This is a guest post by computer scientist Bill Inmon, recognized as the "father of the data warehouse." Bill has written 65 books in nine languages and is currently building a technology called textual ETL.
Many years ago, there were no data warehouses. Most Ecommerce retailers relied on legacy systems with unintegrated data that couldn’t communicate with each other, resulting in data silos. Comparing data sets from these systems was almost impossible. Here are five things you should know about this topic:
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Data warehouses received little support when first created. Only the people who used this technology championed it.
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Businesses tend to focus on analytical tools rather than the data these tools need to generate intelligence.
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Data remains the most critical component of any data warehouse.
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Today, people are skeptical of textual analytics—despite all the business benefits this technology brings.
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Integrate.io is a data warehousing integration solution that can move textual data to a centralized repository for analytics.
One day, the idea of the data warehouse arose, but it received little support from the IT department. Or vendors. Or academics. Data warehouses only received support from the people using them, primarily marketing, sales, and finance teams. Because of this hunger from the user community, the data warehouse has become a standard part of any modern organization.
In this post, learn more about the history of the data warehouse and how Integrate.io can help Ecommerce companies like yours move data from siloed sources to a centralized target system.
Integrate.io is a data warehousing integration solution built for Ecommerce organizations. Use it to move data from multiple sources to a warehouse of your choice with little or no code. Email hello@integrate.io to learn more.
Data Warehouses Were a ‘Hard Sell’
Long before Snowflake and Amazon Redshift, establishing the concept of the data warehouse was a real struggle. There was the complex engineering work involved in designing a warehouse. There was ETL—an alien concept at the time. There were data models. There was a need for a methodology. There was a need for handling volumes of data—the likes of which the world had never before seen. There was a need to recognize and manage dormant data.
To confuse things further, there were even people who came along and built data marts and called them data warehouses. Many people built a data mart, thinking they were building a data warehouse.
When it was all done, when people were creating real data warehouses, analytic vendors like Cognos, MicroStrategy, Business Objects, and the like came along. And here’s the puzzlement: Wall Street valued the analytical companies far greater than the data warehouse infrastructure companies……
Data Is the Most Critical Component of the Data Warehouse
This all reminds me of the building in San Francisco that is tipping over—the Millennium Tower. The story I heard was that one day, one of the owners of one of the million-dollar apartments in the tower dropped a marble on the floor. The marble started rolling toward one of the walls because the multi-story building was tipping over. Not only is that dangerous for the inhabitants of the building but also for the building next door that will need to be demolished when the tipping tower finally falls over. Not to mention the poor pedestrians and street vendors who will be caught in the disaster.
The people who paid all that money for real estate spent their money based on what was above the ground. The apartments looked really cool and sexy. But no one ever looked at the supporting infrastructure underground.
It is that way with a data warehouse. Everyone looks at the cool analytical tools that operate in the data warehouse, and no one pays any attention to the data the analytical tools rely on to generate business insights. That is, they don’t pay attention until the analytical tools start to produce faulty results.
And the real puzzlement is that it took far more toil, risk, and abuse to build the data warehouse environment than it ever did to build the analytical environment. Once the data warehouse was built, it was easy to create visualizations, reports, cubes, and the like.
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Why Is There No Support for Textual Analytics?
The phenomenon above is happening with textual data today. The placing of text into an infrastructure that can be analyzed (textual ETL) is occurring right now, much like the establishment of the data warehouse 20 years ago. However, there is the same skepticism, the same cynicism, and the same lack of understanding and support from IT teams as before. There is no support from the venture capital community, either. Or from academia. The only people championing textual analytics are the end-users. History is repeating itself.
If data warehousing presents incredible business value, textual analytics provides even greater business opportunities. Comparing the value of data warehouses to the value embodied in text is like comparing a BB gun to a hand grenade in terms of power and explosiveness.
And 20 years from now, the world will find that text forms the basis of most data and most decisions in the corporation. People will look back and wonder what all the fuss was about.
How Integrate.io Helps With Textual Data
Data-driven Ecommerce companies use Integrate.io to move textual data to a central repository for analytics without the need for code or complicated big data pipelines. This data warehousing integration solution comes with out-of-the-box connectors that sync with major data warehouses and lakes, removing all the challenges associated with data integration.
Other Integrate.io benefits include world-class customer service, simplified pricing, Salesforce-to-Salesforce integration, and compliance with data compliance legislation.
Integrate.io removes the jargon and pain points of integrating textual data, providing Ecommerce enterprises with ongoing value. Schedule a demo or email hello@Integrate.io to learn more.
Bill Inmon, the father of the data warehouse, has authored 65 books. Computerworld named him one of the ten most influential people in the history of computing.
Bill’s company, Forest Rim Technology, is based in Castle Rock, Colorado. Bill Inmon and Forest Rim Technology help companies hear the voice of their customers. See more at www.forestrimtech.com.