A collection of information technology and consulting knowledge
Category: Information Technology
Information technology (IT) is the use of computers to store, retrieve, transmit, and manipulate data, or information, often in the context of a business or other enterprise. IT is considered to be a subset of information and communications technology (ICT).
In denodo associations follow the same concept as modeling
tools, which can be described as an ‘on-demand join.’
Should Associations Be Created In the Denodo Model?
You don’t necessarily need to define an Association at every
level; usually, the best practice is to apply associations at the following
On final views published for data consumers,
indicating relationships between related views; Especially, on published web
On the component views below, any derived view
that brings together disparate (dissimilar) data sources. The associations should be defined as
Referential Constraints whenever appropriate to aid the optimization engine.
On the component views below, any derived view
that joins a “Base View from Query” with standard views, since Base
Views from Query cannot be rewritten by the denodo optimization engine. Often Base Views from Query create
These best practices should cover the majority scenarios;
beyond these guidelines, it is best to take an ad-hoc approach to create
Associations when you see a specific performance/optimization.
Are Associations important in Denodo?
In a nutshell, associations performance and the efficiency
of the denodo execution optimizer along with other model metadata, such as:
A coworker recently asked a question as to whether denodo
generated joins automatically from source RDBMS database schema. After searching, a few snippets of
information became obvious. First, that
the subject of inheriting join properties was broader than joins and needed to
in modeling associations (joins on demand). Second, that there were some denodo
design best practices to be considered to optimize associations.
Denodo Automatically Generate Joins From the Source System?
After some research, the short answer is no.
Denodo Inherit Accusations From A Logical Model?
The short answer is yes.
Denodo bridges allow models to be passed to and from other
modeling tools, it is possible to have the association build automatically,
using the top-down approach design approach and importing a model, at the
Interface View level, which is the topmost level of the top-down design
However, below the Interface view level, associations and or joins are created manually by the developer.
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
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
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
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.
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.
ETL and EAI
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
Limited data validation
Integrating operations is pull, push,
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
Integrating operation is a pull,
Supports proper profiling and data
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
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
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 has
several benefits, including:
They help team members
have a consistent understanding of the user group.
stakeholders with an opportunity to discuss the critical features of a system
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
What Makes Up a
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
description/quote that best describes the persona as it relates to the product.
Unlike the name and
image, which might be fictitious, the demographic profile includes factual
details about the ideal user. The demographic profile includes:
Age, gender, education, ethnicity, persona group, and family status
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?
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?
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.
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 VARYING (n)
CHARACTER VARYING (n)
DECIMAL (n, m)
NUMERIC (n, m)
TIMESTAMP WITH TIME ZONE
VARCHAR ( MAX )
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.