Business Intelligence – From Backroom to Mission-Critical

BIBackroomToMissionCritical46313508BlogBusiness Intelligence (BI), as we know it today, is an industry that’s been on a wild ride for the last 25 years. It has evolved from the basic idea of a top-down methodology to store data and provide the means for better decision making to full-scale, enterprise-wide, mission-critical systems used by every corporation in the world. BI and its older brother, Data Warehouse (DW), have become necessary components for doing business in the 21st century.

Since we can’t have BI without data, data warehousing is almost always considered to be part of the more general umbrella term of Business Intelligence. Looking at the types of applications available today, BI covers a broad spectrum of software and careers for capturing, storing and analyzing data.

Here are my thoughts on how our industry of equal parts science and imagination made its ascent over the last 25 years.

Historic Publications

In the 1990s William H. Inmon and Ralph Kimball each published books that would change the course of data science:

  • 1992: William H. Inmon publishes the book “Building the Data Warehouse.”
  • 1996 Ralph Kimball publishes the book “The Data Warehouse Toolkit.”

These two data warehousing visionaries arguably did more for data science than any two people in history. Kimball’s book and dimensional modeling methodology gave a new vision of how data should be structured and stored. It also came at a time when technology and hardware were reaching a point where relatively large amounts of data could be stored on a disk rather than on tape as in previous generations.

The Dot-Com Bubble Bursts

The frenzy of the new World Wide Web and allure of becoming an instant millionaire brought more attention to technology than ever before. As a result, the “geek is chic” mindset was born. After the bubble burst in 2000 and the economy came crashing down, the questions from all business leaders and investors were: why did this happen and how can we keep it from happening again? To hedge against future financial catastrophes, many corporations began investing heavily in data warehousing technologies with the promise of making better and more informed decisions.

2001–2002

  • Database vendors such as Oracle, IBM, Microsoft, Teradata and SAP increase development of data warehouse technology.
  • Enterprise reporting software vendors release more powerful tools for analyzing data than existed in the 1990s.
  • The term “dashboards” finds its way into the common IT vernacular, and a generation of analytics professionals is released into the wild.

Major BI Vendor Acquisitions

The early 2000s were a turning point with large-scale BI vendor acquisitions. On the heels of these acquisitions was the financial crisis.

2007

  • Oracle announces in March its plans to acquire Hyperion.
  • SAP announces in October its plans to acquire BusinessObjects.
  • IBM announces in November its plans to acquire Cognos.
  • The “Great Recession” officially begins in December.

2008

  • SAP acquires BusinessObjects
  • IBM acquires Cognos
    • Financial crisis leads to tighter regulation and the need for better data analysis.
    • Cloudera is founded and Hadoop’s meteoric rise to big data fame begins.

The combination of the financial crisis of 2008 and “big BI” vendor acquisitions in 2007–2008 undoubtedly led to better BI software in the coming years.

2009

  • Dashboards become all the rage as functionality and access to data reach an all-time high. Countless blogs begin springing up showcasing creative dashboard designs.
  • Extract, transform, load (ETL) technology continues to play a vital role in data warehousing with products like Informatica and Data Integrator (now known as SAP Data Services).

2010–2014

  • “Big Data” is no longer a fringe segment of BI. In large part, Hadoop can accept much of the credit.
  • Countless Big Data vendors go to market with columnar and in-memory solutions for storing and access large amounts of memory.
  • Data discovery and visualization tools get the spotlight – dashboards get much more advanced when data scientists become involved and begin using new and more powerful tools for analyzing large amounts of complex data.
  • Companies like Tableau, Qlik and BIRST become household names, at least within the business and IT communities. Data analysis has never been so beautiful.

2012

  • Users relying on BI to perform their jobs surpasses the 50 percent mark. This number is expected to increase to 85 percent by 2018.

2013–2015

  • Universities across the country offering Masters of Science degrees in Advanced Analytics, Business Intelligence and Big Data report record numbers of applicants.

2020

  • Expectations are that the industry will continue to grow at a 22 percent increase.

If the next 25 years are anything like the last 25, we can surely expect continued improvements in speed, functionality and capability in all segments of BI. Who will be the next generation’s William H. Inmon and Ralph Kimball? Are you new to BI and DW? Because it’s never too late to start. Take a Global Knowledge training course to discover what’s out there.

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