Hitting The Ceiling
Isn’t it good to have many resources? Why, it is of course. But what if there are too many of them and the specifics of your business is that you have to sort them out in order to pick the most appropriate things? In such a situation the variety of accessible resources means more work, because leaving them unsorted would result in inefficient performance and consequently in loss of competitiveness.
Information is such a resource; and typically only a small percent of information received by us on a daily basis is really helpful for a certain problem. On a personal level everyone does lots of filtering all the time leaving only important things to analyze. But even a small organization receives way more data, making it too challenging to handle in a ‘traditional’ way. In such a situation, when it becomes too difficult to get rid of excessive resources, one definitely needs a new approach.
Big Data received its name (as well as close attention from businesses worldwide) not when the amount of information coming from various sources has hit some score, but when a certain limit of business analysts’ possibilities was reached. But highlighting the problem and making it widely recognized immediately led to appearance of solutions.
BI Solutions For Big Data
Business intelligence is all about mass data analysis and development of decisions basing upon the results of that analysis; so no wonder it is most deeply impacted by the Big Data problem. During the last several years a number of software products entered this market niche.
Maybe the most convenient way to get a quick but informative picture of the current business intelligence software market is addressing Gartner. In its 2013’s ‘Magic Quadrant for Business Intelligence and Analytics Platforms’, the world’s leading researcher traditionally divides BI vendors into four groups; it’s worth noting that the “Visionaries” cell is empty and the “Challengers” cell is almost empty – all the vendors mentioned are almost equally distributed between “Leaders” and “Niche Players”. As many would guess, the prominent IT companies dominate the top right cell: MS, IBM, SAS, and Oracle compose the top by two combined factors: Completeness of Vision and Ability to Execute. Well, it’s no wonder biggest software companies were among the first to experience the impact of huge volumes of data continuously coming from various directions and requiring to be handled ASAP. Still, Gartner points at some weak places in their solutions – mostly related to feature set overcomplexity and issues with upgrading.
Niche leaders surely mustn’t underestimate new challengers – for example, Actuate, which is quite close to the ‘Leaders’ section. According to the report, the company has reached very nice results in 2012. For example, only 4.44% of respondents had complaints about performance of its products, compared to the niche average of 11.5%. License cost however is significantly limiting the growth of Actuate’s popularity. Yet this problem could get eventually solved if further success of the company allows it to utilize more effective marketing tactics.
We have taken a quick glance at the current state of affairs between Big Data and Business Intelligence. Now what’s about the data structuring technologies’ role in this alliance?
Documentation As A Time Savior
One of the most important things in data analytics is that the process of analysis must be logged. The results of analytics must be put into specific documents so that business decision makers could keep them. Furthermore, making decisions basing upon those results always requires some input from managers. Usually it involves some discussions. Thus the decision makers need to exchange knowledge; and here we come again to the importance of documentation.
Today’s BI solutions are therefore naturally to a great extent related to DMS. Improved usability is one of the best practices in BI products development. The general trend is removing any obstacles and additional chain links between an analytics system and its end user (typically an executive manager). This means the data coming from BI systems must be well-structured and clear enough to be used for decisions making. In other words, it must meet actual corporate documentation standards.
Another key value for BI process is its real-time relevance. Companies need quick data for timely decisions to be taken. That’s why their BI systems need DMS. The latter facilitate data storing & retrieving and ideas exchange, helping to produce actual results faster.
As you can see, all three elements not only fit perfectly together, but also form a system, all elements of which enforce each other.
Want to know more about how these elements can help your business? Contact us to discuss.