It is difficult for most businesses to effectively use numerous data of information since enterprise data analysis and management is becoming more difficult and complex. With the growing chances of failure and higher stakes at risk, businesses need to choose the proper software application or software tool that will extract insights from the inside information and manage the database of their enterprise.
What is DBVisualizer?
DBVisualizer is designed as a universal database tool to be used by data analysts, database administrators, and software developers. This software application offers a straightforward and all-in-one UI or user interface for enterprise database management. It comes in both a paid professional edition that provides a wider variation of features and a free edition.
Is DBVisualizer an open-source application?
No, it is a proprietary software application.
Will DBVisualizer run on both Linux and Windows?
DBVisualizer is also dubbed as the universal database tool. It implies that it is capable of running on all of the major operating systems. Hence, the DBVisualizer SQL editor runs smoothly on Windows, Linux/UNIX, and macOS.
Which technical roles would use DBVisualizer most?
Technical roles that deal with databases regularly such as database administrators, developers, and analysts require specific aspects that can be of help to make their work easier. With DBVisualizer, developers can access the advanced DBVisualizer SQL editor that includes smart features that are needed in writing queries, avoiding errors, and speeding up the coding process. For analysts, it will be easier and quicker for them to understand and access the data with the insight feature. They can also easily manage and create the database visually. Lastly, database administrators can be assured that data is secured and preserved during sessions with the autosave feature of DBVisualizer. The software application is also highly optimized and customized to fit the workflow of the user.
Databases or databases types that the DBVisualizer supports
Db2
Exasol
Derby
Amazon Redshift
Informix
H2
Mimer SQL
MariaDB
Microsoft SQL Server
MySQL
Netezza
Oracle
SAP ASE
PostgreSQL
NuoDB
Snowflake
SQLite
Vertica
IBM DB2 LUW
Databases that are accessible with JDBC (Java Database Connectivity) driver is capable of working or running with DBVisualizer. You can also see DBVisualizer’s official website that some users have successfully used the software with other non-official database systems such as IBM DB2 iSeries, Firebird, Teradata, and Hive. Aside from that, you can also see the list of other databases that will soon be supported by DBVisualizer.
What are the most essential DBVisualizer documentation links?
Here are the following links that can cover the basic downloads to the application and basic information.
The business landscape of today is controlled and influenced by big data and it is also getting bigger and bigger as time goes by. Since the amount of data that is needed to be stored and organized is massive, data workers use SQL to access the information in a relational database. Software applications such as SQL clients can let users create SQL queries, access the database’s information, and view the models of relational databases. One of the most famous and sought out option for SQL clients is the SQuirreL SQL Client.
What is SQuirreL SQL?
It is a client for examining and retrieving SQL databases via a user-friendly and simple graphical user interface (GUI). It can run on any computer that has a Java Virtual Machine (JVM) since SQuirreL SQL is a programming language written in Java. You can download the SQuirreL SQL editor for free and is available in different languages such as English, Chinese, German, Russian, Portuguese, French, and Spanish.
Which technical roles would use SQuirreL SQL most?
SQuirreL SQL is useful and convenient for anyone who works on SQL databases regularly such as software developers, database administrators, application administrators, software testers, etc. For application administrators, they can use SQuirreL SQL to fix a bug at the level of the database. Aside from that, correcting and scanning for incorrect values in a table is easy using SQuirreL SQL. It can also help database administrators in overseeing huge varieties of relational databases, checking problems in tables, manage databases using commands, and viewing metadata.
Is it an open-source application?
SQuirreL SQL Client is a single, open-source graphical front end, Java-written program that enables you to issue SQL commands, perform SQL functions, and view the contents of a database. JDBC-compliant databases are supported by the built graphical front end. It also uses the most popular choice for the open-source software which is the GNU General Public License v2.0.
Will SQuirreL SQL run on both Linux and Windows?
SQuirreL is available under an open-source license and a popular Java written SQL database client. It runs under Microsoft Windows, Linux, and macOS.
Here are the supported databases of SQuirreL SQL:
Apache Derby
Hypersonic SQL
Axion Java RDBMS
H2 (DBMS)
ClickHouse
InterBase
Ingres (also OpenIngres)
Informix
InstantDB
IBM DB2 for Windows, Linux, and OS/400
Microsoft SQL Server
Microsoft Access with the JDBC/ODBC bridge
MySQL
Mimer SQL
Mckoi SQL Database
MonetDB
Netezza
Oracle Database 8i, 9i, 10g, 11g
PostgreSQL 7.1.3 and higher
Pointbase
Sybase
SAPDB
Sunopsis XML Driver (JDBC Edition)
Teradata Warehouse
Vertica Analytic Database
Firebird with JayBird JCA/JDBC Driver
What are the most essential SQuirreL SQL documentation links?
With high data volumes and complex systems, database management is becoming more in-demand in today’s economy. Aside from keeping up with the business, organizations also need to innovate new ideas to progress further in the industry. With the use of database management tools, a web interface is provided for database administrators, allowing SQL queries to run.
What is DBeaver?
DBeaver is an open-source universal management tool that can help anyone in professionally working with their data. It will help you maneuver your data similar to a typical spreadsheet, construct analytical reports of various data storage records, and convey information. Effective SQL-editor, connection sessions monitoring, many administration features, and schema and data migration capabilities are imparted with DBeaver’s user on the advanced database. Aside from its usability, it also supports a wide array of databases.
Here are the other offers of DBeaver:
Cloud data sources support
Security standard of enterprise support
Support of multiplatform
Meticulous design and implementation of user interface
Can work with other integration extensions
Will it run on both Linux and Windows?
DBeaver is downloadable for Windows 9/8/10, Mac OS X, and Linux. It requires at least Java 1.8 version, and OpenJDK 11 bundle is already included in DBeaver’s MacOS and Windows installer.
Main features of DBeaver
DBeaver main features include:
Various data sources connection
Edit and view data
Advanced security
Generate mock-data
Built-in SQL editor
Builds the visual query
Transfer data
Compares several database structures
Search metadata
And generates schema/database ER diagrams.
Which databases or database types does DBeaver support?
More than 80 databases are supported by DBeaver, and it includes some of the well-known databases such as:
Data Modeling is an established technique of comprehensively documenting an application or software system with the aid of symbols and diagrams. It is an abstract methodology of organizing the numerous data elements and thoroughly highlighting how these elements relate to each other. Representing the data requirements and elements of a database gra phically is called an Entity Relationship Diagram, or ERD.
What is an Entity?
Entities are one of the three essential components of ERDs and represent the tables of the database. An entity is something that depicts only one information concept. For instance, order and customer, although related, are two different concepts, and hence are modeled as two separate entities.
A data model entity typically falls in one of five classes – locations, things. events, roles, and concepts. Examples of entities can be vendors, customers, and products. These entities also have some attributes associated with them, which are some of the details that we would want to track about these entities.
A particular example of an entity is referred to as an instance. Instances form the various rows or records of the table. For instance, if there is a table titled ‘students,’ then a student named William Tell will be a single record of the table.
Why Do We Need a Data Model Entity?
Data is often stored in various forms. An organization may store data in XML files, spreadsheets, reports, and relational databases. Such a fragmented data storage methodology can present challenges during application design and data access. Writing maintainable and efficient code becomes all the more difficult when one has to think about easy data access, scalability, and storage. Additionally, moving data from one form to the other is difficult. This is where the Entity Data Model comes in. Describing the data in the form of relationships and entities, the structure of the data becomes independent of the storage methodology. As the application and data evolve, so does the Data Model Entity. The abstract view allows for a much more streamlined method of transforming or moving data.
The SQL LENGTH function returns the number of characters in a string. The LENGTH function is available in many Database Management Systems (DBMS).
The LENGTH Function Syntax
LENGTH(string)
LENGTH Function Notes
If the input string is empty, the LENGTH returns 0.
If the input string is NULL, the LENGTH returns NULL.
Length Function Across Databases
When working as a technical consultant, one has to work with customer’s databases and as you move from one database to another you will find that the function commands may vary–assuming the database has an equivalent function.
Working with VQL and SQL Server got me thing about the LENGTH() function, so, here is a quick references list, which does include the SQL Server.
Data Virtualization is an information management technique which combines different locations, data format, data structure and/or application data sources into a single “virtual” unifying semantics layer that provides integrated data services to consuming applications or users in real-time. Basically, data virtualization offers Data as a Service (Daas), providing a centralized point for consumption.
Data Warehousing, Extract Transform, and Load, ETL process
What is a Data Warehouse
The description of what a data warehouse is varies greatly. The definition that I give that seems to work is that a data warehouse a database repository that supports system interfaces, reporting and business analysis, data integration and domain normalization, and structure optimization. The structure can vary greatly depending the school of thought used to construct the data warehouse and will have at least one data mart.
What a data warehouse is:
A source of data and enriched information used for reporting and business analysis.
A repository of metadata that organizes data into hierarchies used in reporting and analysis
What a data warehouse is not:
A reporting application in and of itself; it is used by other applications to provide reporting and analysis.
An exact copy of all tables/data in the source systems. Only those portions of source system tables/data required to support reporting and analysis are moved into data warehouse.
An Online Transaction Processing (OLTP) system.
An archiving tool. Data is kept in data warehouse in accordance with the data retention guidelines and/or as long as need to support frequently used reporting and analysis needs.
Whenever a new application is in development, unit testing is a vital part of the process and is typically performed by the developer. During this process, sections of code are isolated at a time and are systematically checked to ensure correctness, efficiency, and quality. There are numerous benefits to unit testing, several of which are outlined below.
1. Maximizing Agile Programming and Refactoring
During the coding process, a programmer has to keep in mind a myriad of factors to ensure that the final product correct and as lightweight, as is possible for it to be. However, the programmer also needs to make certain that if changes become necessary, refactoring can be safely and easily done.
Unit testing is the simplest way to assist in making for agile programming and refactoring because the isolated sections of code have already been tested for accuracy and help to minimize refactoring risks.
2. Find and Eliminate Any Bugs Early in the Process
Ultimately, the goal is to find no bugs and no issues to correct, right? But unit testing is there to ensure that any existing bugs are found early on so that they can be addressed and corrected before additional coding is layered on. While it might not feel like a positive thing to have a unit test reveal a problem, it’s good that it’s catching the issue now so that the bug doesn’t affect the final product.
3. Document Any and All Changes
Unit testing provides documentation for each section of coding that has been separated, allowing those who haven’t already directly worked with the code to locate and understand each individual section as necessary. This is invaluable in helping developers understand unit APIs without too much hassle.
4. Reduce Development Costs
As one can imagine, fixing problems after the product is complete is both time-consuming and costly. Not only do you have to sort back through a fully coded application’s worth of material, any bugs which may have been compounded and repeated throughout the application. Unit testing helps not only limit the amount of work that needs to be done after the application is completed it also reduces the time it takes to fix errors because it prevents developers from having to fix the same problem more than once.
5. Assists in Planning
Thanks to the documentation aspect of unit testing, developers are forced to think through the design of each individual section of code so that its function is determined before it’s written. This can prevent redundancies, incomplete sections, and nonsensical functions because it encourages better planning. Developers who implement unit testing in their applications will ultimately improve their creative and coding abilities thanks to this aspect of the process.
Conclusion
Unit testing is absolutely vital to the development process. It streamlines the debugging process and makes it more efficient, saves on time and costs for the developers, and even helps developers and programmers improve their craft through strategic planning. Without unit testing, people would inevitably wind up spending far more time on correcting problems within the code, which is both inefficient and incredibly frustrating. Using unit tests is a must in the development of any application.
While researching an old install for an upgrade system
requirement compliance, I discovered that I b=need to validate which Linux
version was installed. So, here is a
quick note on the command I used to validate which version of Linux was
installed.
A semantic data model is a method of organizing and representing corporate data that reflects the meaning and relationships among data items. This method of organizing data helps end users access data autonomously using familiar business terms such as revenue, product, or customer via the BI (business intelligence) and other analytics tools. The use of a semantic model offers a consolidated, unified view of data across the business allowing end-users to obtain valuable insights quickly from large, complex, and diverse data sets.
What is the purpose
of semantic data modeling in BI and data virtualization?
A semantic data model sits between a reporting tool and the original database in order to assist end-users with reporting. It is the main entry point for accessing data for most organizations when they are running ad hoc queries or creating reports and dashboards. It facilitates reporting and improvements in various areas, such as:
No relationships or joins for end-users to worry about because they’ve already been handled in the semantic data model
Data such as invoice data, salesforce data, and inventory data have all been pre-integrated for end-users to consume.
Columns have been renamed into user-friendly names such as Invoice Amount as opposed to INVAMT.
The model includes powerful time-oriented calculations such as Percentage in sales since last quarter, sales year-to-date, and sales increase year over year.
Business logic and calculations are centralized in the semantic data model in order to reduce the risk of incorrect recalculations.
Data security can be incorporated. This might include exposing certain measurements to only authorized end-users and/or standard row-level security.
A well-designed semantic data model with agile tooling allows end-users to learn and understand how altering their queries results in different outcomes. It also gives them independence from IT while having confidence that their results are correct.
Over recent years, business
enterprises relying on accurate and consistent data to make informed decisions
have been gravitating towards integration technologies. The subject of
Enterprise Application Integration (EAI) and Extraction, Transformation &
Loading (ETL) lately seems to pop up in most Enterprise Information Management
conversations.
From an architectural perspective,
both techniques share a striking similarity. However, they essentially serve
different purposes when it comes to information management. We’ve decided to do
a little bit of research and establish the differences between the two
integration technologies.
Enterprise
Application Integration
Enterprise Application Integration (EAI) is an integration framework that consists of technologies and services, allowing for seamless coordination of vital systems, processes, as well as databases across an enterprise.
Simply put, this integration
technique simplifies and automates your business processes to a whole new level
without necessarily having to make major changes to your existing data
structures or applications.
With EAI, your business can
integrate essential systems like supply chain management, customer relationship
management, business intelligence, enterprise resource planning, and payroll.
Well, the linking of these apps can be done at the back end via APIs or the
front end GUI.
The systems in question might use
different databases, computer languages, exist on different operating systems
or older systems that might not be supported by the vendor anymore.
The objective of EAI is to develop a
single, unified view of enterprise data and information, as well as ensure the
information is correctly stored, transmitted, and reflected. It enables
existing applications to communicate and share data in real-time.
Extraction,
Transformation & Loading
The general purpose of an ETL system
is to extract data out of one or more source databases and then transfer it to
a target destination system for better user decision making. Data in the target
system is usually presented differently from the sources.
The extracted data goes through the
transformation phase, which involves checking for data integrity and converting
the data into a proper storage format or structure. It is then moved into other
systems for analysis or querying function.
With data loading, it typically
involves writing data into the target database destination like data warehouse
and operational data store.
ETL can integrate data from multiple
systems. The systems we’re talking about in this case are often hosted on
separate computer hardware or supported by different vendors.
Differences between
ETL and EAI
EAI System
Retrieves small amounts of data in
one operation and is characterized by a high number of transactions
EAI system is utilized for process
optimization and workflow
The system does not require user
involvement after it’s implemented
Ensures a bi-directional data flow
between the source and target applications
Ideal for real-time business data
needs
Limited data validation
Integrating operations is pull, push,
and event-driven.
ETL System
It is a one-way process of creating
a historical record from homogeneous or heterogeneous sources
Mainly designed to process large
batches of data from source systems
Requires extensive user involvement
Meta-data driven complex
transformations
Integrating operation is a pull,
query-driven
Supports proper profiling and data
cleaning
Limited messaging capabilities
Both integration technologies are an
essential part of EIM, as they provide strong capabilities for business
intelligence initiatives and reporting. They can be used differently and
sometimes in mutual consolidation.
Personas and roles are
user modeling approaches that are applied in the early stages of system
development or redesign. They drive the design decision and allows programmers
and designers to place everyday user needs at the forefront of their system
development journey in a user-centered design approach.
Personas and user roles
help improve the quality of user experience when working with products that
require a significant amount of user interaction. But there is a distinct
difference between technology personas vs. roles. What then exactly is a
persona? What are user roles in system development? And, how does persona
differ from user roles?
Let’s see how these two
distinct, yet often confused, user models fit in a holistic user-centered
design process and how you can leverage them to identify valuable product
features.
Technology Personas
Vs. Roles – The Most Relevant Way to Describe Users
In software development,
a user role describes the relationship between a user type and a software tool.
It is generally the user’s responsibility when using a system or the specific
behavior of a user who is participating in a business process. Think of roles
as the umbrella, homogeneous constructs of the users of a particular system.
For instance, in an accounting system, you can have roles such as accountant,
cashier, and so forth.
However, by merely using
roles, system developers, designers, and testers do not have sufficient
information to conclusively make critical UX decisions that would make the
software more user-centric, and more appealing to its target users.
This lack of
understanding of the user community has led to the need for teams to move
beyond role-based requirements and focus more on subsets of the system users.
User roles can be refined further by creating “user stand-ins,” known as
personas. By using personas, developers and designers can move closer to the
needs and preferences of the user in a more profound manner than they would by
merely relying on user roles.
In product development,
user personas are an archetype of a fictitious user that represents a specific
group of your typical everyday users. First introduced by Alan Cooper, personas
help the development team to clearly understand the context in which the ideal
customer interacts with a software/system and helps guide the design decision
process.
Ideally, personas
provide team members with a name, a face, and a description for each user role.
By using personas, you’re typically personalizing the user roles, and by so
doing, you end up creating a lasting impression on the entire team. Through
personas, team members can ask questions about the users.
The Benefits of
Persona Development
Persona development has
several benefits, including:
They help team members
have a consistent understanding of the user group.
They provide
stakeholders with an opportunity to discuss the critical features of a system
redesign.
Personas help designers
to develop user-centric products that have functions and features that the
market already demands.
A persona helps to
create more empathy and a better understanding of the person that will be using
the end product. This way, the developers can design the product with the
actual user needs in mind.
Personas can help
predict the needs, behaviors, and possible reactions of the users to the
product.
What Makes Up a
Well-Defined Persona?
Once you’ve identified
user roles that are relevant to your product, you’ll need to create personas
for each. A well-defined persona should ideally take into consideration the
needs, goals, and observed behaviors of your target audience. This will
influence the features and design elements you choose for your system.
The user persona should
encompass all the critical details about your ideal user and should be
presented in a memorable way that everyone in the team can identify with and
understand. It should contain four critical pieces of information.
1. The header
The header aid in
improving memorability and creating a connection between the design team and
the user. The header should include:
A fictional name
An image, avatar or a
stock photo
A vivid
description/quote that best describes the persona as it relates to the product.
2. Demographic
Profile
Unlike the name and
image, which might be fictitious, the demographic profile includes factual
details about the ideal user. The demographic profile includes:
Personal background:
Age, gender, education, ethnicity, persona group, and family status
Professional background:
Occupation, work experience, and income level.
User environment. It
represents the social, physical, and technological context of the user. It
answers questions like: What devices do the user have? Do they interact with
other people? How do they spend their time?
Psychographics:
Attitudes, motivations, interests, and user pain points.
3. End Goal(s)
End goals help answer
the questions: What problems or needs will the product solution to the user?
What are the motivating factors that inspire the user’s actions?
4. Scenario
This is a narrative that
describes how the ideal user would interact with your product in real-life to
achieve their end goals. It should explain the when, the where, and the how.
Conclusion
For a truly successful
user-centered design approach, system development teams should use personas to
provide simple descriptions of key user roles. While a distinct difference
exists in technology personas vs. roles, design teams should use the two
user-centered design tools throughout the project to decide and evaluate the
functionality of their end product. This way, they can deliver a useful and
usable solution to their target market.
denodo 7.0 saves some manual coding when building the ‘Base Views’ by performing some initial data type conversions from ANSI SQL type to denodo Virtual DataPort data types. So, where is a quick reference mapping to show to what the denodo Virtual DataPort Data Type mappings are:
ANSI SQL types To Virtual DataPort Data types Mapping
ANSI SQL Type
Virtual DataPort Type
BIT (n)
blob
BIT VARYING (n)
blob
BOOL
boolean
BYTEA
blob
CHAR (n)
text
CHARACTER (n)
text
CHARACTER VARYING (n)
text
DATE
localdate
DECIMAL
double
DECIMAL (n)
double
DECIMAL (n, m)
double
DOUBLE PRECISION
double
FLOAT
float
FLOAT4
float
FLOAT8
double
INT2
int
INT4
int
INT8
long
INTEGER
int
NCHAR (n)
text
NUMERIC
double
NUMERIC (n)
double
NUMERIC (n, m)
double
NVARCHAR (n)
text
REAL
float
SMALLINT
int
TEXT
text
TIMESTAMP
timestamp
TIMESTAMP WITH TIME ZONE
timestamptz
TIMESTAMPTZ
timestamptz
TIME
time
TIMETZ
time
VARBIT
blob
VARCHAR
text
VARCHAR ( MAX )
text
VARCHAR (n)
text
ANSI SQL Type Conversion Notes
The function CAST truncates the output when converting a value to a text, when these two conditions are met:
You specify a SQL type with a length for the target data type. E.g. VARCHAR(20).
And, this length is lower than the length of the input value.
When casting a boolean to an integer, true is mapped to 1 and false to 0.
Every day, businesses
are creating around 2.5 quintillion bytes of data, making it increasingly
difficult to make sense and get valuable information from this data. And while
this data can reveal a lot about customer bases, users, and market patterns and
trends, if not tamed and analyzed, this data is just useless. Therefore, for
organizations to realize the full value of this big data, it has to be
processed. This way, businesses can pull powerful insights from this stockpile
of bits.
And thanks to artificial
intelligence and machine learning, we can now do away with mundane spreadsheets
as a tool to process data. Through the various AI and ML-enabled data analytics
models, we can now transform the vast volumes of data into actionable insights
that businesses can use to scale operational goals, increase savings, drive
efficiency and comply with industry-specific requirements.
We can broadly classify
data analytics into three distinct models:
Descriptive
Predictive
Prescriptive
Let’s examine each of
these analytics models and their applications.
Descriptive
Analytics. A Look Into What happened?
How can an organization
or an industry understand what happened in the past to make decisions for the
future? Well, through descriptive analytics.
Descriptive analytics is
the gateway to the past. It helps us gain insights into what has happened.
Descriptive analytics allows organizations to look at historical data and gain
actionable insights that can be used to make decisions for “the now” and the
future, upon further analysis.
For many businesses, descriptive analytics is at the core of their everyday processes. It is the basis for setting goals. For instance, descriptive analytics can be used to set goals for a better customer experience. By looking at the number of tickets raised in the past and their resolutions, businesses can use ticketing trends to plan for the future.
Some everyday applications of descriptive analytics include:
Reporting of new trends
and disruptive market changes
Tabulation of social
metrics such as the number of tweets, followers gained over some time, or
Facebook likes garnered on a post.
Summarizing past events
such as customer retention, regional sales, or marketing campaigns success.
To enhance their decision-making
capabilities businesses have to reduce the data further to allow them to make
better future predictions. That’s where predictive analytics comes in.
Predictive
Analytics takes Descriptive Data One Step Further
Using both new and
historical data sets predictive analytics to help businesses model and forecast
what might happen in the future. Using various data mining and statistical
algorithms, we can leverage the power of AI and machine learning to analyze
currently available data and model it to make predictions about future
behaviors, trends, risks, and opportunities. The goal is to go beyond the data
surface of “what has happened and why it has happened” and identify what will
happen.
Predictive data
analytics allows organizations to be prepared and become more proactive, and
therefore make decisions based on data and not assumptions. It is a robust
model that is being used by businesses to increase their competitiveness and
protect their bottom line.
The predictive
analytics process is a step-by-step process that requires analysts to:
Define project
deliverables and business objectives
Collect historical and
new transactional data
Analyze the data to
identify useful information. This analysis can be through inspection, data
cleaning, data transformation, and data modeling.
Use various statistical
models to test and validate the assumptions.
Create accurate
predictive models about the future.
Deploy the data to guide
your day-to-data actions and decision-making processes.
Manage and monitor the
model performance to ensure that you’re getting the expected results.
Instances Where
Predictive Analytics Can be Used
Propel marketing
campaigns and reach customer service objectives.
Improve operations by
forecasting inventory and managing resources optimally.
Fraud detection such as
false insurance claims or inaccurate credit applications
Risk management and
assessment
Determine the best
direct marketing strategies and identify the most appropriate channels.
Help in underwriting by
predicting the chances of bankruptcy, default, or illness.
Health care: Use
predictive analytics to determine health-related risk and make informed
clinical support decisions.
Prescriptive
Analytics: Developing Actionable Insights from Descriptive Data
Prescriptive analytics
helps us to find the best course of action for a given situation. By studying
interactions between the past, the present, and the possible future scenarios,
prescriptive analytics can provide businesses with the decision-making power to
take advantage of future opportunities while minimizing risks.
Using Artificial
Intelligence (AI) and Machine Learning (ML), we can use prescriptive analytics
to automatically process new data sets as they are available and provide the
most viable decision options in a manner beyond any human capabilities.
When effectively used,
it can help businesses avoid the immediate uncertainties resulting from
changing conditions by providing them with fact-based best and worst-case
scenarios. It can help organizations limit their risks, prevent fraud,
fast-track business goals, increase operational efficiencies, and create more
loyal customers.
Bringing It All
Together
As
you can see, different big data analytics models can help you add more sense to
raw, complex data by leveraging AI and machine learning. When effectively done,
descriptive, predictive, and prescriptive analytics can help businesses realize
better efficiencies, allocate resources more wisely, and deliver superior
customer success most cost-effectively. But ideally, if you wish to gain
meaningful insights from predictive or even prescriptive analytics, you must
start with descriptive analytics and then build up from there.
Descriptive vs Predictive vs Prescriptive Analytics
Occasionally, I need to update the windows hosts files, but I seem to have a permanent memory block where the file is located. I have written the location into numerous documents, however, every time I need to verify and or up the host file I need to look up the path. Today, when I went to look it up I discovered that I had not actually posted it to this blog site. So, for future reference, I am adding it now.
Here is the path of the Windows Hosts file, the drive letter may change depending on the drive letter on which the Windows install was performed.
A Denodo virtualization project typically classifies the
project duties of the primary implementation team into four Primary roles.
Denodo Data Virtualization Project Roles
Data Virtualization Architect
Denodo Platform Administrator
Data Virtualization Developer
Denodo Platform Java Programmer
Data Virtualization Internal Support Team
Role To
Project Team Member Alignment
While the denodo project is grouped into security permissions and a set of duties, it is import to note that the assignment of the roles can be very dynamic as to their assignment among project team members. Which team member who performs a given role can change the lifecycle of a denodo project. One team member may hold more than one role at any given time or acquire or lose roles based on the needs of the project.
Denodo
virtualization Project Roles Duties
Data Virtualization
Architect
The knowledge, responsibilities, and duties of a denodo data
virtualization architect, include:
A Deep understanding of denodo security features
and data governance
Define and document5 best practices for users,
roles, and security permissions.
Have a strong understanding of enterprise
data/information assets
Defines data virtualization architecture and
deployments
Guides the definition and documentation of the
virtual data model, including, delivery modes, data sources, data combination,
and transformations
Denodo Platform
Administrator
The knowledge, responsibilities, and duties of a Denodo Platform
Administrator, Include:
Denodo Platform Installation and maintenance, such as,
Installs denodo platform servers
Defines denodo platform update and upgrade policies
Creates, edits, and removes environments, clusters, and servs
Manages denodo licenses
Defines denodo platform backup policies
Defines procedures for artifact promotion between environments
Denodo platform configuration and management, such as,
Configures denodo platform server ports
Platform memory configuration and Java Virtual Machine (VM) options
Set the maximum number of concurrent requests
Set up database configuration
Specific cache server
Authentication configuration for users connecting to denodo platform (e.g., LDAP)
Secures (SSL) communications connections of denodo components
Provides connectivity credentials details for clients tools/applications (JDBC, ODBC,,,etc.)
Configuration of resources.
Setup Version Control System (VCS) configuration for denodo
Creates new Virtual Databases
Create Users, roles, and assigns privileges/roles.
Execute diagnostics and monitoring operations, analyzes logs and identifies potentials issues
Manages load balances variables
Data Virtualization
Developer
The Data Virtualization Developer role is divided into the
following sub-roles:
Data Engineer
Business Developer
Application Developer
the knowledge, responsibilities, and duties of a Denodo Data
Virtualization Developer, by sub-role, Include:
Data Engineer
The denodo data engineer’s duties include:
Implements the virtual data model construction
view by
Importing data sources and creating base views,
and
Creating derived views applying combinations and
transformations to the datasets
Writes documentation, defines testing to eliminate
development errors before code promotion to other environments
Business Developer
The denodo business developer’s duties include:
Creates business vies for a specific business
area from derived and/or interface views
Implements data services delivery
Writes documentation
Application Developer
The denodo application developer’s duties include:
Creates reporting vies from business views for
reports and or datasets frequently consumed by users
Writes documentation
Denodo Platform Java
Programmer
The Denodo Platform Java Programmer role is an optional,
specialized, role, which:
Creates custom denodo components, such as data sources, stored procedures, and VDP/iTPilot functions.
Implements custom filters in data routines
Tests and debugs any custom components using Denodo4e
Data Virtualization
Internal Support Team
The denodo data virtualization internal support team’s duties
include
Access to and knowledge of the use and trouble
of developed solutions
Tools and procedures to manage and support
project users and developers
Information Technology (IT) Skill badges are becoming more prevalent in the information technology industry, but do they add value? I will be in the past I have only bothered with certifications where my clients or my employer thought they were valuable. At some point in your career experience should mean more tests and training. So, perhaps is time to consider the potential value of IT Skills badges (Mini-certification) and the merits behind them.
What Are Information
Technology (IT) Skills Badge?
IT Skills badges are recognized as
mini-certification, which are portable. IT Skills badges are achieved when an
individual completes a project, completes a course, or make a distinguished
contribution towards code repository on either GitHub or elsewhere. When a
person earns this kind of certification, the IT Skills badges can be stored in
a digital wallet. An individual can use it by either including it to his/her
LinkedIn profile or website. The issuer has the authority of editing the
badges. This feature is designed to bolster credibility.
Research shows that many IT job
applicants show badges as an added advantage in his/her skills. IT skills badge
are not a sure bet in job hunting that an applicant will land on that
particular job because most job recruiters don’t focus on them.
Many IT industries want validated skills
before hiring an applicant. IT Skills badges are complementary to certificates,
but IT Skills badges can’t in any way replace certifications. Individuals with
convectional certifications have high chances of landing on premium pay. As a
result, badges don’t ensure the owner a pay boot in his/her job.
How Do IT Skills
Badges Differ From A Certification?
Certifications are considered evidence
by many of an individual’s skills. Does this mean that any other credential
systems aren’t necessary for proving your skills? IBM’s study shows that
technology is growing at a faster rate in areas like artificial intelligence,
big data, and machine learning and the updating and creation of certifications
can lag because of the time required to update or developing certifications is
lengthy.
Another difference when it comes to
comparison between IT Skill Badges and certification is that certifications are
seen to be more expensive to both employers and employees. It is costly to
achieve certification, and a lot of study time and books may be required. An
in-depth done survey shows that employers are willing to pay a good portion to
the right certification. Certificate value is drastically increasing value
yearly as compared to badges.
Clients of IT companies consider
engaging in a contract with the company after making sure that the company has
a specific number of employees with specified certifications. IT Skills badges
are at a disadvantage for hiring consideration. Most hiring managers, the likes
of Raxter Company, don’t know the benefit of badges or even what IT Skills
badges can do with IT Skills badges. IT Skills badges are new in the market;
hence, most employers have little information about IT Skills badges. For
instance, an applicant who in the past years has worked for IBM Company
presents an IBM badge to Raxter interview panel, and the panel will not know
what it means.
In the case of Grexo Technology
Group’s CEO, Bobby Yates, IT services Company in Texas doesn’t know the
apparent value of IT skills badge. He further challenges it by saying that most
applicants have presented the badges to him. But he surely doesn’t know the
importance of them towards his requirements from the applicants. He further
says that he doesn’t consider badges as a valuable hiring tool as compared to
certification.
Dupray’s Tremblay, on the other hand, seconds the elimination of badges as an essential tool for hiring by saying that he will not know if the applicant is cheating to him. As a result, he values the certification as a real prove of skills towards IT.
How To Obtain IT Skills Badges
Most Companies’ hiring panels
consider IT Skills badges as nothing towards job requirements. But some
companies’ managers like O’Farril and others challenge them by finding them
worthy when it comes to IT workers investment. CompTIA’s Stanger, on the other
hand, backs badges by referring to them as a complement to a basket of
certifications, good resumes, and real-world towards job experience. He adds by
saying that it is a form of strengthening the education chain. Raxter on his
personality considers IT Skills badges as a selling point. As a result, IT
Skills badges are essential to present to some recruiters.
The following are
the top five tips that will aid an individual towards his carrier advancement
in getting the most in IT skills badges.
1. Avoid listing badges which are
easily obtained. Anything that can take less than 40 hours to complete it is
unworthy of mentioning it in your professional resume.
2. Always consider those courses
that directly aline with the type of jobs for which you are applying. IT skills
badges that directly complements to your job requirements are worth taking.
Irrelevant badges may, to an extent, reduce the chances of being recruited.
3. Make sure to pair the badges
attained with your education or real working experience.
4. Don’t insist on the importance
behind your badges. Not everybody will like to hear. Real work experience
always takes the lead.
5. If you can’t defend your knowledge,
experience, and skills or hiring managers will consider unqualified. ITSkill
badges and certifications show that you had enough knowledge to pass the qualifications,
but employees want people who can and will excel at doing the work as part of a
team. requirements
Do IT Skills badges have value in the hiring process?
IT skills complement IT certification and act as an added advantage in hiring panel, mostly when your certification is almost similar to the other candidates. IT Skills badges add some value towards a good resume, real job experience, and certifications. Some recruiters consider IT Skills badges worthy when it comes to the hiring process. Recruiters think them as a selling point.
So it’s essential to take IT Skills
badges that relate to your job application to spice your application form.
Remember to keep in mind the top five tips when you decide to have one. In
other words, IT Skills badges are somehow worthwhile to consider in IT workers
investments.
IT skills badge from a social media perspective
Social Media badges are virtual
validator of successful completion of a task, skill, or educational objective. IT
Skills badges can either be physical or digital depending upon what other
people in a particular community value or market. IT Skills badges are more
prevalent in a collaborative environment, and social media as well as portals
and learning platforms, including team participation, certification, degrees,
and project accomplishments.
In conclusion, many IT skills are
available for your earnings. To gain more on IT Skills badges, you can visit
IBM, Pearson VUE, a global learning company, and others who have partnered in
offering IT Skills badges. You will be able to find a range of IT Skills badges
from which to choose.
PostgreSQL is an open-source database, which was released in
1996. So, PostgreSQL has been around a long time. So, among the many companies and industries
which know they are using PostgreSQL, many others are using PostgreSQL and
don’t know it because it is embedded as the foundation in some other
application’s software architecture.
I hadn’t paid much attaint to PostgreSQL even though it as
been on the list leading databases used by business for years. Mostly I have been focused on the databases
my customer were using (Oracle, DB2, Microsoft SQL Server, and MySQL/MariaDB). However, during a recent meeting I was
surprised to learn that io had been using and administering PostrgresSQL embedded
as part of another software vendors application, which made me take the time to
pay attention to PostgreSQL. Especially, who is using PostgreSQL and what opportunities
that may provide for evolving my career?
The
Industries Using PostgreSQL
According to enlyft,
the major using the PostgreSQL are Computer Software and Information Technology
And services companies.
PostgreSQL Consumers Information
Here is the link to
enlyft page, which provides additional information companies and industries
using PostgreSQL:
How to get a list of installed InfoSphere Information (IIS) Server products
Which File contains the list of Installed IIS products?
The list of installed products can be obtained from the Version.xml file.
Where is the Version.xml file located?
The exact location of the Version.xml document depends on the operating system in use and where IIS was installed to, which is normally the default location of:
Well, this is one of those circumstances, where your ability
to answer this question will depend upon your user’s assigned security roles
and what you actually want.
To get a complete list, you will need to use the DBA_
administrator tables to which most of us will not have access. In the very simple examples below, you may
want to add a WHERE clause to eliminate the system schemas from the list, like
‘SYS’ and ‘SYSTEM,’ if you have access to them.
Example
Administrator (DBA) Schema List
SELECT distinct OWNER as SCHEMA_NAME
FROM DBA_OBJECTS
ORDER BY OWNER;
Example Administrator
(DBA) Schema List Results Screenshot
Example Administrator (DBA) Schema List Results Screenshot
Fortunately for the rest of us, there are All user tables,
from which we can get a listing of the schemas to which we have access.
Example
All Users Schema List
SELECT distinct OWNER as SCHEMA_NAME
FROM ALL_OBJECTS
ORDER BY OWNER;
Example All Users
Schema List Results Screenshot
Example All Users Schema List Results Screenshot
Related
References
Oracle help Center
> Database> Oracle > Oracle Database > Release 19
It is funny how you cannot work with some for a while
because of newer tools, and then rediscover them, so to speak. The other day I was looking at my overflow
bookshelf in the garage and saw an old book on Oracle SQL*Plus and was thinking,
“do I still want or need that book?”.
In recent years I have been using a variety of other tools
when working with oracle. So, I really hadn’t thought about the once ubiquitous
Oracle SQL*Plus command-line interface for Oracle databases, which around for
thirty-five years or more. However, I
recently needed to do an Oracle 18C database install to enable some training
and was pleasantly surprised Oracle SQL*Plus as a menu item.
Now I have been purposely using Oracle SQL*Plus again to refresh my skills, and I will be keeping my Oracle SQL*Plus: The Definitive Guide, after all.
Oracle provides a few ways to determine which database you are working in. Admittedly, I usually know which database I’m working in, but recently I did an Oracle Database Express Edition (XE) install which did not goes has expected and I had reason to confirm which database I was actually in when the SQL*Plus session opened. So, this lead me to consider how one would prove exactly which database they were connected to. As it happens, Oracle has a few ways to quickly display which database you are connected to and here are two easy ways to find out your Oracle database name in SQL*Plus:
V$DATABASE
GLOBAL_NAME
Checking
the GLOBAL_NAME table
The First method is to run a quick-select against the GLOBAL_NAME
table, which. is publicly available to logged-in users of the database
Example GLOBAL_NAME Select Statement
select * from global_name;
Example GLOBAL_NAME Select Statement
Checking
the V$DATABASE Variable
The second method is to run a quick-select a V$database.
However, not everyone will have access to the V$database variable.
The “Set Number” command in the VI (visual instrument) text
editor seems may not seem like the most useful command. However, it is more useful than it
appears. Using the “set number” command
is a visual aid, which facilitates navigation within the VI editor.
To
Enable Line Number In the VI Editor
The “set Number” command is used to make display line
numbers, to enable line numbers:
Press the Esc key within the VI editor, if you
are currently in insert or append mode.
Press the colon key “:”, which will appear at
the lower-left corner of the screen.
Following the colon enter “set number” command
(without quotes) and press enter.
A column of sequential line numbers will then appear at the
left side of the screen. Each line number references the text located directly
to the right. Now you will know exactly which line is where and be able to enter
a colon and the line number you want to move to and move around the document
lines with certainty.
To
Disable Line Number In the VI Editor
When you are ready to turn offline numbering, again follow
the preceding instructions, except this time, enter the following line at the :
prompt:
Press the Esc key within the VI editor, if you
are currently in insert or append mode.
Press the colon key “:”, which will appear at
the lower-left corner of the screen.
Following the colon enter “set nonumber” command
(without quotes) and press enter.
To Make The Line
Number Enable When You Open VI:
Normally, vi will forget the setting you’ve chosen once you’ve left the editor. You can, however, make the “set Number” command take effect automatically whenever you use vi on a user/account, enter the “set Number” command as a line in the .exrc file in your home directory.
Today,
data-driven decision making is at the center of all things. The emergence of
data science and machine learning has further reinforced the importance of data
as the most critical commodity in today’s world. From FAAMG (the biggest five
tech companies: Facebook, Amazon, Apple, Microsoft, and Google) to governments
and non-profits, everyone is busy leveraging the power of data to achieve final
goals. Unfortunately, this growing demand for data has exposed the inefficiency
of the current systems to support the ever-growing data needs. This
inefficiency is what led to the evolution of what we today know as Logical Data
Lakes.
What Is a Logical
Data Lake?
In
simple words, a data lake is a data repository that is capable of storing any
data in its original format. As opposed to traditional data sources that
use the ETL (Extract, Transform, and Load) strategy, data lakes work on the ELT
(Extract, Load, and Transform) strategy. This means data does not have to be
first transformed and then loaded, which essentially translates into reduced
time and efforts. Logical data lakes have captured the attention of
millions as they do away with the need to integrate data from different data
repositories. Thus, with this open access to data, companies can now begin to
draw correlations between separate data entities and use this exercise to their
advantage.
Primary Use Case
Scenarios of Data Lakes
Logical data lakes are a
relatively new concept, and thus, readers can benefit from some knowledge of
how logical data lakes can be used in real-life scenarios.
To conduct
Experimental Analysis of Data:
Logical data lakes can
play an essential role in the experimental analysis of data to establish its
value. Since data lakes work on the ELT strategy, they grant deftness and speed
to processes during such experiments.
To store and
analyze IoT Data:
Logical data lakes can
efficiently store the Internet of Things type of data. Data lakes are capable
of storing both relational as well as non-relational data. Under logical data
lakes, it is not mandatory to define the structure or schema of the data
stored. Moreover, logical data lakes can run analytics on IoT data and come up
with ways to enhance quality and reduce operational cost.
To improve Customer
Interaction:
Logical data lakes can
methodically combine CRM data with social media analytics to give businesses an
understanding of customer behavior as well as customer churn and its various
causes.
To create a Data
Warehouse:
Logical data lakes
contain raw data. Data warehouses, on the other hand, store structured and
filtered data. Creating a data lake is the first step in the process of data
warehouse creation. A data lake may also be used to augment a data warehouse.
To support
reporting and analytical function:
Data lakes can also be
used to support the reporting and analytical function in organizations. By
storing maximum data in a single repository, logical data lakes make it easier
to analyze all data to come up with relevant and valuable findings.
A logical data lake is a comparatively new area of study. However, it can be said with certainty that logical data lakes will revolutionize the traditional data theories.
The private cloud concept is running the cloud software architecture and, possibly specialized hardware, within a companies’ own facilities and support by the customer’s own employees, rather than having it hosted from a data center operated by commercial providers like Amazon, IBM Microsoft, or Oracle.
A companies’
private (internal) cloud may be a one or more of these patterns and may be part
of a larger hybrid-cloud strategy.
Home-Grown, where the company has built its own software and or hardware could infrastructure where the private could is managed entirely by the companies’ resources.
Commercial-Off-The-Self (COTS), where the cloud software and or hardware is purchased from a commercial vendor and install in the companies promises where is it is primarily managed by the companies’ resources with licensed technical support from the vendor.
Appliance-Centric, where vendor specialty hardware and software are pre-assembled and pre-optimized, usually on proprietary databases to support a specific cloud strategic.
Hybrid-Cloud, which may use some or all of the about approaches and have added components such as:
Virtualization software to integrate, private-cloud, public-cloud, and non-cloud information resources into a central delivery architecture.
Public/Private cloud where proprietary and customer sensitive information is kept on promise and less sensitive information is housed in one or more public clouds. The Public/Private hybrid-cloud strategy can also be provision temporary short duration increases in computational resources or where application and information development occur in the private cloud and migrated to a public cloud for productionalization.
In the modern technological era, there are a variety of cloud patterns, but this explanation highlights the major aspects of the private cloud concept which should clarify and assist in strategizing for your enterprise cloud.
Data virtualization is a data management approach that allows retrieving and manipulation of data without requiring technical data details like where the data is physically located or how the data is formatted at the source. Denodo is a data virtualization platform that offers more use cases than those supported by many data virtualization products available today. The platform supports a variety of operational, big data, web integration, and typical data management use cases helpful to technical and business teams. By offering real-time access to comprehensive information, Denodo helps businesses across industries execute complex processes efficiently. Here are 10 Denodo data virtualization use cases.
1. Big data analytics
Denodo is a popular data virtualization tool for examining large data sets to uncover hidden patterns, market trends, and unknown correlations, among other analytical information that can help in making informed decisions.
2. Mainstream business intelligence and data warehousing
Denodo can collect corporate data from external data sources and operational systems to allow data consolidation, analysis as well as reporting to present actionable information to executives for better decision making. In this use case, the tool can offer real-time reporting, logical data warehouse, hybrid data virtualization, data warehouse extension, among many other related applications.
3. Data discovery
Denodo can also be used for self-service business intelligence and reporting as well as “What If” analytics.
4. Agile application development
Data services requiring software development where requirements and solutions keep evolving via the collaborative effort of different teams and end-users can also benefit from Denodo. Examples include Agile service-oriented architecture and BPM (business process management) development, Agile portal & collaboration development as well as Agile mobile & cloud application development.
5. Data abstraction for modernization and migration
Denodo also comes in handy when reducing big data sets to allow for data migration and modernizations. Specific applications for this use case include, but aren’t limited to data consolidation processes in mergers and acquisitions, legacy application modernization and data migration to the cloud.
6. B2B data services & integration
Denodo also supports big data services for business partners. The platform can integrate data via web automation.
7. Cloud, web and B2B integration
Denodo can also be used in social media integration, competitive BI, web extraction, cloud application integration, cloud data services, and B2B integration via web automation.
8. Data management & data services infrastructure
Denodo can be used for unified data governance, providing a canonical view of data, enterprise data services, virtual MDM, and enterprise business data glossary.
9. Single view application
The platform can also be used for call centers, product catalogs, and vertical-specific data applications.
10. Agile business intelligence
Last but not least, Denodo can be used in business intelligence projects to improve inefficiencies of traditional business intelligence. The platform can develop methodologies that enhance outcomes of business intelligence initiatives. Denodo can help businesses adapt to ever-changing business needs. Agile business intelligence ensures business intelligence teams and managers make better decisions in shorter periods.
Related References
Denodo > Data Virtualization Use Cases And Patterns
AIX (Advanced Interactive eXecutive) is an operating system developed by IBM for business all across the world that needs data metrics that can keep up with the ever-changing scope of business in today’s world. AIX is a version of UNIX. AIX is designed to work on a number of computer platforms from the same manufacturer. On its launch, the system was designed for IBM’s RT PC RISC workstation.
User interface
AIX was developed with Bourne Shell
as the default shell for three versions of the OS. Afterwards, it was changed
to KornShell going forward from version 4. The OS uses Common Desktop
Environment (CDE) as the default user interface for graphics. The System
Management Interface Tool on the OS allows users to access the menu using a
hierarchy of commands instead of the command line.
Compatible systems
The operating system works on a number of hardware platforms. The initial OS was designed for the IBM RT PC and used a microkernel that controlled the mouse, disk drives, keyboard, and display. This allowed users to use all these components between operating systems by the use of a hot key-the alt+tab combination. The OS was also fitted on newer systems such as the IBM PS/2 series, IDM mainframes, AI-64 systems and can also be used with the Apple’s server network. AIX is commonly used on IBM’s 64-bit POWER processor and systems. AIX can run most Linux applications (after recompiling) and has full support for Java 2.
Since its introduction to computer infrastructure, the operating system has undergone a lot of upgrades with five versions released since 2001. The latest version of the software is the AIX 7.2. All of these come with a high tech security system and fast uptimes.
As an operating system AIX has become popular with students who learn quickly by working on AIX projects live. Working professionals have also been attracted by the dependability of the system and the intuitive that is part of its design.
Cloud computing is a service driven model for enabling ubiquitous, convenient, on demand network access to a shared pool computing resources that can be rapidly provisioned and released with minimal administrative effort or service provider interaction.
