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A Race Towards Pervasive Analytics
Gartner’s top 10 trends for 2010 set the stage for Cloud computing and Analytics.
Analytics is context driven, and presents actionable results to the business user. BI allows the user to slice and dice data. BI is good if you know what you are looking for. The reason Gartner placed analytics above BI is because of the needs of businesses today to act on data, as opposed to merely having access to it. There is way too much data. We do not need systems that create more data – we need intelligence from the data, which is what Analytics does. Hence the positioning of Analytics on the Gartner charts.
BI has become pervasive, as it should be. It has even entered open source with Pentaho and Jaspersoft, a sure sign of being pervasive! However, this was inevitable as every business user needs easy access to their data. A recent survey conducted by B Eye Network involving more than 1,000 respondents from around the globe found that only 12 percent said they had no plans to use open source software in some form for business intelligence applications or data warehouses.
However – converting the data to intelligence, and actionable intelligence in the next frontier. That is why Gartner placed Analytics in their top 10 trends chart, and moved BI out! As we have watched with Google analytics, the analytics on web traffic data is pervasive. There are a myriad of products that provide analytics on web stats, but Google provides a universal product ensuring that everyone has access to it.
Analytics on corporate data will also become pervasive. Companies are demanding this. The analytics will be contextual, as this is required for analytics to automatically make sense out of data. The analytics will be agile and companies will be able to pour their data in, and watch the results take shape. Much like Google analytics on web traffic data.
Emcien’s analytics offers analytics on sales data. The context is sales and customer buying patterns. Companies can now pour the sales data and watch the customer buying patterns emerge. No data mapping and model building. No long implementation cycles! The ability to “just turn on and use” is key to being pervasive.
The future is here!
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Why the need for Intuitive analytics?
I just finished meeting with Kathy, a customer who is very analytical and has done an amazing job delivering value on data intelligence for her company. I spend an hour with her and she described the process of implementing tools to gain value from data. “This has been a painful process of exploration” she said. “We are a team of analytical types, and we love to play in the data. Not all companies can afford a team like this. In my last company we could not afford it. And companies cannot compete effectively if they cannot gain intelligence from their data!”
I asked her the challenges with the project and lessons learned. Kathy is a data genius, and there are very few folks like her. Here are some of the points that she made.
- “What am I supposed to do?” The analytics tool needs to answer this question for the business user. It also needs to be very easy to use and understand. This comment reminded me of another conversation with a BI user, and his pet peeves with his BI tools – “I do not know what question to ask!” He said. “Asking intelligent questions is most of the task!”
- Tools for Business Users. Not R&D. Not IT. Kathy went on to comment about the dire need for tools for the Business Users. Companies are running very lean. The last rounds of corporate downsizing have been brutal. Typically, the first teams to go are the analysts and R&D teams. Hence, if the tools are hard to use, now they will never get used. Business leaders are getting smart and they want tools that their line-of-business folks can use. This can help them get value in the line of business.
- Actionable Results. The old slice-and-dice data capability is not useful. Ask may questions and I will answer. The business units are too busy and do not have time to “play in the data”. The tools need to intuitive and give you actionable tasks.
- Like Google Analytics – The words “Analytics” is always associated with webs stats. That is the most commonly understood context of the word. However, there is far more data residing and building up in companies, than there is web traffic and search strings data. We need the same level of analytics, easy to use and intuitive tools for corporate data as we have for the web stats. Analytics means computing a relevant result and presenting easy to understand solutions. Like Google analytics for web traffic. Google analytics presents analytics on web stats; very domain specific, turn it on and off you go! Analytics for companies needs to be like that. Domain specific. Turn it on. Go Live. Get results. Get value!
- Need to think like B2C apps. This was an important point. Why do business users have ugly, clunky software that is expensive to implement and difficult to use? How can they be effective making those million dollar decisions? When the new wave of kids, who grew up with iPods and Facebook, enter the work force, will they throw out all the clunky enterprise apps? Absolutely!! Replace them with with easy to use, Facebook like apps. Business analytics needs to be that easy to use.
Great opportunities! We need to build applications with the user in mind. What will business applications learn from iPod, Facebook, Linkedin, ……
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