ETL tools selection guide for Indian BI pros

Doing research to select an ETL tool? Here is all the ammunition you may need—from ETL checklists to tool kits to case studies to aid your selection.

Procuring extract, transform, and load (ETL) tools for your business is a challenging task. It involves coordinated effort of data warehousing team and the users. To do it effectively, the DW team needs to fully comprehend the processes of moving, reformatting, and cleansing data. The in-depth knowledge resources contained in this guide will aid you in your selection and implementation of ETL tool.

Carefully read the instructions given in the sections below to know the loopholes and missteps before you spend your money. Do not let the vendors misguide or fool you. Learn also from India specific examples and case studies.


ETL tools checklist at your table

Choosing the perfect ETL tool for your organization could be an uphill task given the data integration challenges it may involve. Our integration expert, Jill Dyche from Baseline Consulting, provides you with the information you will need about what to look for in ETL tools and cautions about the mistakes to avoid.


How to identify the suitable option

While procuring an extract, transform, and load (ETL) tool, your considerations should include data formats, profiling, data quality, and meta data support, to name a few. It’s important that the tool you choose is capable of carrying out the functions of moving the data, reformatting it, and cleansing it successfully. Use these detailed tips before investing in an ETL tool for your company.


A rating scale for ETL tools

Are you evaluating ETL tools for your organization? Here is a fresh, new perspective. This section will help you rate the extract, transform and load (ETL) tools and assign weightages to the features. Simplify your tool selection process with this matrix.

Shoppers Stop’s ETL best practices revealed

Building an enterprise data warehouse is critical as it involves integration of data spread across multiple sources and reformatting it. Further uniformly cleaning the data is task. In this section we bring you six extract, transform, and load best practices followed by Shoppers Stop while building its enterprise data warehouse.


A chapter from the ETL-DW Bible

The constituents of a data warehouse are often misunderstood. It is important that any misconceptions the data warehouse team, and especially of the ETL team, should be removed. We therefore provide you with an excerpt from The Data Warehouse ETL Toolkit by Ralph Kimball and Joe Caserta. This authoritative text on ETL has several useful techniques for extracting, cleaning, conforming, and delivering data.


Can ETL tools manage complex business logic?

Worried about ETL tools being able to handle complex business logic? Our experts provide you with an answer to this commonly expressed concern. Learn about what an ETL tool is capable of doing in this section.


Pros and cons of custom development vs. ETL tools

Facing the ‘custom development vs. an ETL tool’ dilemma? Creation of a data warehouse puts organizations in a tough spot while weighing the pros and cons of custom development or an ETL tool. Ian Abramson, Director, Enterprise Data Group, Thoughtcorp, a data warehousing expert, lays down the advantages and disadvantages of both these options to help you make your decision.


Large Indian retailer speeds up sales data manipulation with ETL

Learn how leading retail player Shoppers Stop leveraged sales data. Discover how the company reduced the time taken by business intelligence applications to reflect searches with the help of ETL.



Read more on Data warehousing