What would it be like to have a doctor who’s always up on the latest research and has learned about treatments from over 1.5 million previous cases? It would look alot like Watson, IBM’s Jeopardy! playing supercomputer that’s getting ready to roll out with an all new look and a Memorial Sloan Kettering Cancer Center education in oncology.
How Big Data is Killing Business Intelligence
Business intelligence is dying.
"But," you say, "I thought data was hotter than hot!" And you are correct.
The amount of data available is exploding like never before, and within that data valuable knowledge is hiding. New insights, new ideas, explanations for long-burning questions, it's all there waiting to be discovered and there's the problem.
Business Intelligence struggles with Big Data.
Traditional business intelligence vendors are struggling to keep up. Their tools aren't designed to sift through Big Data. They cannot identify what is meaningful and what should be ignored. They simply present reports on all of it, which quickly becomes a hairy mess of charts, graphs, and grids. They are attempting to update their tools to keep up with Big Data by duct-taping on tools like Hadoop. But with products build for a data world unlike our current reality, these measures are not enough. The volume of data quickly shows BI for what it is: outdated. BI simply cannot put Big Data to work for its customers.
Fortunately, there are new tools becoming available which fill this gap. Companies like Tableau are creating solutions which make it easy to explore data and find answers. We classify these types of tools as "Data Discovery" tools--they make it easy (or at least, easier) to find the interesting data within the mountains of available data.
The analytics market is bifurcating--splitting into two segments: the old "business intelligence" market and the new "data discovery" market. Garnter Research speaks to this in their latest Business Intelligence Magic Quadrant report:
Data discovery alternatives to enterprise BI platforms offer highly interactive and graphical user interfaces built on in-memory architectures to address business users' unmet ease-of-use and rapid deployment needs. What began as a market buying trend in 2010 has only continued to expand. Sales results for vendors in this sector have been stellar and well above the market average. The two branches of BI can be defined as follows:
- Enterprise BI platforms:
- Key buyers: IT.
- Main sellers: megavendors, large independents.
- Approach: top-down, IT-modeled (semantic layers), query existing repositories.
- User interface: report/KPI dashboard/grid.
- Use case: monitoring, reporting.
- Deployment: consultants.
- Data discovery platforms:
- Key buyers: business.
- Main sellers: small, fast-growing independents.
- Approach: bottom-up, business-user-mapped (mashup), move data into dedicated repository.
- User interface: visualization.
- Use case: analysis.
- Deployment: users.
The chasm between these segments continues to deepen because business users find the benefits of using data discovery tools so compelling.
We agree completely with Gartner, and we believe that this trend will only accelerate over the medium-to-long-term. Data discovery capabilities will become increasingly important as the amount of data continues to increase and the traditional business intelligence fails to keep up.
For more on the bifurcation of this market you can read the entire Garnter business intelligence magic quadrant report for free online.
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