Business Intelligence 2.0: Simpler, More Accessible, Inevitable
Say goodbye to complicated interfaces, disconnected analytics and shelfware. An emerging era for BI will bring simplicity, broad access and better ties between analysis and action.
Close the Loop
Today, analytics is a singular process. An individual views a report in some form or creates a query to understand something. No matter how sophisticated or nave, the result is always the same (assuming it works); the analyst has informed his or her opinion or hypothesis, but the analytical tool stops there. It isn't possible to replay the steps and show others how the question was resolved. Nor is it possible, without a custom-made application, to transfer this new knowledge to a system or service that can act on it immediately. Nor is it possible -- again, without building an application -- to track the results of the decision explicitly (as in, "Orville, the action you took on pricing based on the new parameters that entered the system on Tuesday are showing a marked improvement in on-time arrivals at the terminal."). Delivering such capabilities would bring a Nirvana of decision support, something we have all been envisioning for a decade or more, but BI in its current state is not designed to close the loop. That's the promise of BI 2.0, and, in fact, it's the single driving reason for this new era to emerge.
Try New Thinking
Learning new skills is important and it's easy. What's difficult is wrapping your brain around all of this and getting ready to walk away from what you now accept as the correct approach. For instance, here are six BI 1.0 fallacies that fall by the wayside in the BI 2.0 era:
BI 1.0 Fallacies
BI 2.0 Realities
Most users want to be spoon-fed information and will never take the initiative to create their own environment or investigate the best way to get the answers they need.
The Consumer Web invalidates this idea. When given simple tools to do something that is important and/or useful to them, people find a way to "mash up" what they need.
Vendors will obfuscate and slow down the drive for simpler and more affordable tools to preserve their bases
They will, but demographics will pressure them. Most BI "users" will be members of a generation that lives in technology and will reject the functionality of current BI
Only air traffic controllers and credit card approval applications need real-time data
The availability of fresh data, from ever-widening sources, generates its own demand
Analytics cannot be supported until there is an enterprise data warehouse, with a metadata repository, data stewards and a comprehensive data model that represents the "single version of the truth."
Data comprehension will displace data warehousing, to some extent. The single version of the truth will give way to context, contingency and the need to relate information quickly from many sources
Operational systems cannot be queried for analytics
There is no longer a good reason for this prohibition. In fact, with SOA, it doesn't even make sense.
Data must exist in a persistent data store for analytics
Message queues, logs, sensors transient data and caches, temporary aggregates, lingering partial results files all of these can be leveraged now with the resources at hand.
The Agile ArchiveWhen it comes to managing data, donít look at backup and archiving systems as burdens and cost centers. A well-designed archive can enhance data protection and restores, ease search and e-discovery efforts, and save money by intelligently moving data from expensive primary storage systems.
2014 Analytics, BI, and Information Management SurveyITís tried for years to simplify data analytics and business intelligence efforts. Have visual analysis tools and Hadoop and NoSQL databases helped? Respondents to our 2014 InformationWeek Analytics, Business Intelligence, and Information Management Survey have a mixed outlook.
InformationWeek Tech Digest, Nov. 10, 2014Just 30% of respondents to our new survey say their companies are very or extremely effective at identifying critical data and analyzing it to make decisions, down from 42% in 2013. What gives?