Published on Jan 13,2018
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Companies that build data warehouses and use business intelligence for decision-making ultimately save money and increase profit. This is just the tip of the iceberg as there are many more crucial reasons for integrating Data Warehousing with Business Intelligence. This webinar has discussed why Data Warehousing and Business Intelligence go hand-in-hand and many more points.

This specialized webinar introduces you to the main components of a data warehouse and business intelligence. Through this webinar you can learn the following:

  • What is Data Warehousing & Business Intelligence?
  • What is Data Warehousing Architecture?

  • What is Data Modelling / Introduction to ER Win r9 Tool?

  • What is ETL / An Open Source ETL Tool – Talend 5.x?

  • What is Business Intelligence / An Open Source Tableau Public 9.x?

Let’s start off with the basics:

What is Data Warehouse?

In a layman’s term, a data warehouse refers to a database that is maintained separately from an organization’s operational database. According to the official W.H. Inmon, a data warehouse is a subject-oriented, integrated, time-variant, and nonvolatile collection of data in support of management’s decision-making process.

And according to Ralph Kimball, Data warehouse is the conglomerate of all data marts within the enterprise and Information is always stored in the dimensional model.

There are two variants when it comes to the definition of ‘Data Warehouse’. Let’s do a quick comparison of both these versions.

What is Business Intelligence?

Business intelligence a.k.a BI is the set of techniques and tools for the transformation of raw / production and operational data into meaningful and useful information for business analysis purposes for various level. Business intelligence talks about how traditional data which transform into the BI have multiple initiatives to measure, manage, and improve the performance of individuals, processes, teams, and business units for the specific business area.

During the operation of business, the following questions must be asked as the functions of monitoring, analyzing, and planning delve into these questions:

  • What has happened?

  • What is happening?

  • Why?

  • What will happen?

  • What do we need for it to happen?

What are the Business Intelligence categories?

Strategic Business Intelligence:  Management collaborates and agrees on a strategy and a method in which they would like to see information presented, for example, in maps, scorecards, reports, or dashboards.  Now that a strategy has been defined, it is imperative that something is being done with the data that has been collected.

Analytical Business Intelligence: Once Strategic BI sets the foundation in the form of key performance metrics, then Analytical BI is employed to identify the source of an issue once it has been uncovered.

Tools like analytic dashboards, OLAP, predictive analytics, and ad hoc queries are utilized to determine the location or the cause of a major problem.

Data Warehousing Products:

Entity Relationship / Schema Modeling – CA ERwin:

ERwin is a popular data modeling tool used by a number of major companies throughout the world. The product is currently owned, developed, and marketed by Computer Associates, a leading software company. The product supports a variety of aspects of database design, including data modeling, forward engineering (the creation of a database schema and physical database on the basis of a data model), and reverse engineering (the creation of a data model on the basis of an existing database) for a wide variety of relational DBMS, including Microsoft Access, Oracle, DB2, Sybase, and others.

Physical ER Diagram:

Data Integration / ETL – Talend Open DI Studio 5.x:

Talend Open Studio for Data Integration operates as a code generator, producing data transformation scripts and underlying programs in Java. Its GUI gives access to a metadata repository and to a graphical designer. The metadata repository contains the definitions and configuration for each job – but not the actual data being transformed or moved. All of the components of Talend Open Studio for Data Integration use the information in the metadata repository.

Talend Open DI Studio typically used for the following:

  • Synchronization or replication of databases

  • Right-time or batch exchanges of data

  • ETL (Extract/Transform/Load) for analytics

  • Data migration

  • Complex data transformation and loading

  • Data quality exercises

  • Big Data

Talend Open Studio for Data Integration primarily differs from Talend Enterprise Data Integration in that the Enterprise version has a Subversion plug-in built in, as well as support for joblets. Using Talend Enterprise Data Integration, ETL and ELT jobs can have a dynamic schema.

Data visualization With Tableau:

Data visualization tools allow anyone to organize and present information intuitively. This is becoming more vital as data proliferates in every field from bar codes in retail stores to player behavior in online games.

All of this data is meaningless without a way to organize and present important findings within it. People comprehend data better through pictures than by reading numbers in rows and columns.

So by visualizing data, you are able to more effectively ask and answer important questions such as “Where are sales growing,” “What is driving growth” and “What are the characteristics of my customers using different services?” By using Tableau visualizations, you gain the ability to quickly answer questions; your data becomes a competitive advantage instead of an underutilized asset.

Open Source VS Commercial ETL Tools:

Questions asked during the webinar:

1. Advantages of using Tableau over commercial tools:

  • Usability – Helps you explore and present data in an easier and faster manner than before

  • Faster Performance – Individual performance improvements in Tableau 9.0 combine to provide unprecedented overall speed increases across workbooks.

  • Analytics in the Flow – Gives instant visual feedback and answers deeper questions.

  • Smart Maps – Answer geographic questions more easily.

  • Data Preparation – Connecting to spreadsheets is fast and easy.

2. Which one is better: Tableau or Qlikview?

It all depends on the purpose. It’s more like which suits what. Here is the comparison Qlikview, Tableau and Spotfire.

3. What is the difference between global and local repository?

GlobalRepository  – Domain can contain one global repository. The global repository can contain common objects to be shared throughout the domain through global shortcuts.

Local Repository – Each local repository in the domain can connect to the global repository and use objects in its shared folders. A folder in a local repository can be copied to other local repositories while keeping all local and global shortcuts intact.

You can check out the webinar PPT as well.

Got more questions for us? Please mention them in the comments section and we will get back to you.

Related Posts:

Importance and Benefits of Data Warehousing

ETL Using Big Data Talend

Get Started With Mastering Data Warehousing and Business Intelligence

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