Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    image fx (60)
    Data Analytics Driving the Modern E-commerce Warehouse
    13 Min Read
    big data analytics in transporation
    Turning Data Into Decisions: How Analytics Improves Transportation Strategy
    3 Min Read
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Data Integration: Hand-coding Using ETL Tools
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Warehousing > Data Integration: Hand-coding Using ETL Tools
Data Warehousing

Data Integration: Hand-coding Using ETL Tools

RickSherman
RickSherman
5 Min Read
SHARE

Hand-stop We are creatures of habit. It’s not easy to stop doing something the way we’ve always done it. Especially when we think we are right (but actually we’re not). Let’s explain.

I have discussed (some might say preached) in many posts, articles, webinars, podcasts, classes and client discussions that for any recurring data integration tasks IT should use an Extract, Transform and Load (ETL)  tool.

This certainly has been the best practice for enterprise data warehousing projects in the Fortune 1000. This is where I got my early experience in data integration and got to use the ETL tools that annually rank in Gartner’s Upper Magic Quadrant and Forrester’s Top Wave. These ETL tools enabled IT groups and SI (system integrator) project teams to tackle data integration challenges too complex and extensive for hand-coding. 

However, while the enterprise data warehousing projects were being developed with enterprise class ETL tools, most Fortune 1000 departmental projects and small to medium business (SMB) companies were hand-coding their data-integration processes.

More Read

“Storage Dreams” and the greatest things since sliced bread!
TDWI Boston Chapter Meeting – January 14: Maintaining Security, Privacy, and Accountability in DW/BI Implementations
Business of Carbon Management from Special Reports
EmSense, a “neuromarketing” company founded in 2004 by seven…
Video

IT groups choose to hand-code because for quite a while the enterprise class ETL tools they heard of were too …



Hand-stop We are creatures of habit. It’s not easy to stop doing something the way we’ve always done it. Especially when we think we are right (but actually we’re not). Let’s explain.

I have discussed (some might say preached) in many posts, articles, webinars, podcasts, classes and client discussions that for any recurring data integration tasks IT should use an Extract, Transform and Load (ETL)  tool.

This certainly has been the best practice for enterprise data warehousing projects in the Fortune 1000. This is where I got my early experience in data integration and got to use the ETL tools that annually rank in Gartner’s Upper Magic Quadrant and Forrester’s Top Wave. These ETL tools enabled IT groups and SI (system integrator) project teams to tackle data integration challenges too complex and extensive for hand-coding. 

However, while the enterprise data warehousing projects were being developed with enterprise class ETL tools, most Fortune 1000 departmental projects and small to medium business (SMB) companies were hand-coding their data-integration processes.

IT groups choose to hand-code because for quite a while the enterprise class ETL tools they heard of were too expensive for their budgets. In addition, these tools required dedicated, trained developers. Life in a small IT group means doing multiple tasks and never really having time to get training. The result is millions of lines of hand-coded ETL in enterprises today —  most of which is not documented and took much longer to develop than it would have with an ETL tool.

Times are Changing

But times have changed. There are now very robust, affordable ETL tools that can easily handle any departmental or SMB data integration projects (and might even be able to handle some enterprise data warehouses too).

In fact, two classes of ETL tools are free (or almost so). First, database vendors have “bundled” ETL tools with their databases. Although initially these tools were very simplistic they have expanded over the years have quite robust functionality. Second, open source software (OSS) ETL tools have also emerged and are capable of handling many departmental and SMB needs.

The emergence of these tools has broken through the pricing barrier with ETL tools that are not only quite capable, but not difficult for a small IT staff to learn. I have been advocating these tools in the departmental and SMB data integration market for years. The good news is these tools are picking up converts but the bad news is IT may not be using these tools as well as they might.

Stay tuned for my next post, where I continue this discussion with Hand-Coding: What Went Wrong and How to Avoid Repeating History’s Mistakes


Link to original post

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Why the AI Race Is Being Decided at the Dataset Level
Why the AI Race Is Being Decided at the Dataset Level
Artificial Intelligence Big Data Exclusive
image fx (60)
Data Analytics Driving the Modern E-commerce Warehouse
Analytics Big Data Exclusive
ai for building crypto banks
Building Your Own Crypto Bank with AI
Blockchain Exclusive
julia taubitz vn5s g5spky unsplash
Benefits of AI in Nursing Education Amid Medicaid Cuts
Artificial Intelligence Exclusive News

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Tackling Big Data on Police Use of Force

10 Min Read

As RFID (radio frequency identity tagging) expands into more…

1 Min Read

When does a hard science become a team sport?

4 Min Read

Eye-Fi: Your Digital Photographic Memory

2 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

AI and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive
AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?