Business Intelligence History
When did Business Intelligence first come into play?
Before the Information Age of the late 20th century companies had to collect their information from non-automated sources. Those were the days that businesses lacked any type of sophisticated computing resources to enable them to properly analyze data.
Due to the lack of today’s flourishing technologies organizations in that age made vital business decisions based purely on instinct, this could very often prove to be a fatal means of making a decision that concerned the well-being or livelihood of an organization.
The 1970s kicked off the beginning of the End-User Computing era, even so the complex world of technologies was in all fairness a bit too much for the normal human being to deal with. Years ago End-Users had to wait for everything, they had to wait for their systems, for programming changes, and even for reports.
They spent most of their time waiting for something, or rather anything, to emerge from central programming and computer sites. It is no secret that this time could have been better spent in analysis.
The earlier tools designed for query and reporting were sold as do-it-yourself solutions, though the idea was fascinating the solutions at times did very little solving at all. That was the way of Business Intelligence until in the mid-1970s several of the leading Business Intelligence vendors began offering tools that allowed even a non-programmer to plunge into the world of data access and analysis. Though by that time nearly every vendor’s product set included core exclusive data formats, which only served to complicate matters more so.
One undeniable reason for the new formatting was to provide the End-User with the power to generate his own data and to place that data into an arrangement that would be prime for the tool. A different reason was that the period of interpersonal databases had not yet proven themselves for conventional usage or implementation of end-user data, so the vendors were obligated to offer their own data solutions.
There were palpable uncertainties with such data sources such as: they were inaccessible and exclusive, they functioned only with that vendor’s tool, most were unable contain the girth of data needed, IT support was essential to pull information from the original source, and a hefty investment into these tools could cut off or shut in relevant data used within a tool that might later drop behind the fast pace in which technology was evolving.
What challenges were present with earlier Business Intelligence systems?
Throughout the growth of Business Intelligence vendors automated more systems, expanding the amount of data available. Yet the process of collection remained a troublesome challenge due to lack of a sufficient infrastructure for data exchange or to unharmonious systems.
Perhaps one of the most daunting challenges was the endless months it took to analyze and report on the massive amounts data that had been gathered. Though the process of decision making for the long term was greatly improved, short term tactical decisions were still made mostly on sheer intuition.
When did Business Intelligence begin to truly shine?
With the dawn of personal computers Business Intelligence began to take off with a zealous that no one could have expected. Once we began integrating analysis and processing programs into the personal computer the world changed as we knew it.
Endless possibilities were at the fingertips of programmers. The ability to use your own personal machine to analyze and crunch numbers endlessly was a giant leap forward. This ability took a lot of the waiting out of the analyzing and reporting process.
The next step was a short lived one, this was the new idea of Information Warehousing. Though the concept itself was brilliant, the data was never converted into clear information, the idea was simply to leave it as it was and where it was but access it from anywhere with the early Business Intelligence tools.
This new step posed a few challenges like the data was presented as is and any errors had to be address by the user, this allotted time that could have been best spent elsewhere. In addition to the ragged condition of the data it also had to be pulled from various sources, which produced an extreme amount of data.
On the other hand there was one substantially positive aspect given birth through information warehousing era and that was the new realization of the need for a very strong requirement for metadata.
After the information warehousing fad quickly died away the Data Warehousing era took effect. This era introduce a way not only to reorganize data but to transform it into a much cleaner and easier to follow form. Data Warehousing is actually a set of processes designed to extract, clean, and reorganize data, enabling users to get a clearer idea of exactly what kind of data they are dealing with and it’s relevance to the issue they are addressing.
Has Business Intelligence reached its peak?
All in all we have leapt and bound over the years where Business Intelligence is concerned. In the early years we leaned that that user-friendly language could close the gap between the end users and the IT environment opening a line of communication that would simplify the relationship between the two if only a little.
Centralized centers were a created as a means to inspire more productivity from end-users and the need to set more specific standards for analysis tools could take the growth of Business Intelligence much further in the direction of creating a viable and productive system
Then with the dawn of the client/server era we learned rather harshly that keeping our data in situ was not beneficial to analysis, but instead we found that reformatting the data would prove to be the most fruitful approach. Following this discovery we entered the information warehousing age, which taught us the importance of capturing metadata in its existing form so we could investigate what the data contained before and after its transformation.
Even with all of the advancement that the late 1980’s brought Business Intelligence it is with the Data Warehousing era I believe we took the biggest steps in the right direction. This era bought to our attention the importance of taking existing data and transforming it into a new analysis based data.
With this new discovery we also learned that such a transformation could prove to be costly and time consuming, even so if used correctly by those who truly needed the technology the benefit would undoubtedly out weigh the cost. Perhaps the most momentous aspect of warehousing is the understanding that the back ends will most likely linger and processes to transform and create new data stores will need to be automated.
Now we enter an era where packaged Business Intelligence systems are on demand. The drive behind this is mostly due to management, who need to have the sophisticated analyses and metrics delivered to them in a clean and clear manner.
Business Intelligence has come a very long way, but just as most technologies it continues to evolve and give way to more productive and desirable tools. The only question that remains about its evolution is where the demand for Business Intelligence will take us in the future of data analysis and collection technology.