Monday Apr 09, 2012

Polyglot Analytics

Just like polyglot persistence, where a variety of data stores exist to handle a wide variety of data persistency requirements for different data management use cases, we are now seeing the emergence of a variety of BI and analytic solutions for delivering insight on all types of data. In the context of polyglot persistence, Oracle not only offers the number one relational database solution in the market today, we also deliver market leading NoSQL and In-Memory (TimesTen) as well as our Essbase OLAP engine where they serve as excellent solutions for handling a variety of persistency requirements. Of course, we've had a strong track record of also delivering enterprise class business intelligence and reporting solutions to the market and now have extended the BI and Analytics offering with Oracle Endeca Information Discovery, a data discovery solution that enables one to quickly explore all relevant data whether structured, semi-structured or unstructured in nature. And just like polyglot persistence solutions that compliment one another, we also see the same case for polyglot analytics. Our Business Intelligence solutions complement each other. In fact, they solve different problems and create different kinds of value. Why Polyglot Analytics exist. In a sense, its no different than programmers using different language to tackle different requirements and use cases. As an example, it would not be unusual for server side code to be written in Java while a web page is driven by Javascript or even Ruby. 

Business Intelligence clearly provides proven answers to known questions while out extensions, in this case, Data Discovery, it provides fast answers to new questions formulated by the business user. For example, when the business intelligence report says that warranty claims on the top-selling product went up 15% last month, the new questions are “What changed? What’s the root cause? What are customers saying about this? That exploration happens in a discovery app.

And the relationship goes both ways. Data Discovery creates new KPIs for the BI stack to deliver. For example, a consumer packaged goods company learned that preference for seemingly unrelated brands was highly correlated in certain customer segments. This came from a social media discovery app and suggested new KPIs they quickly pulled into their operational BI system.

Far from replacing their BI systems with data discovery, our customers have instead been able to get far MORE value out of their existing BI systems because they are able to re-focus them on solving the problems they are most effective for, and creating new practices around data discovery to get fast answers to new questions.

Just like NoSQL solutions solve different problems than relational databases, Data Discovery solves new problems that are different than traditional business intelligence and reporting:

The fact that data is available immediately creates demand for it. As more application, consumer, sensor, and mobile data is available to the business, the more the business wants to use that varied data for daily decisions that today get made on intuition and opinion.
In analytics, big variety is a bigger problem than big volume because it can’t be solved by more processing power alone. In addition, the cost and time required to combine diverse data together must come down.
The people making these decisions are experts in the business, not in writing SQL queries. They need a user experience that’s simple to learn and use and this is a core capability of Oracle Endeca Information Discovery. 

It combines structured and unstructured data from inside or outside the company. An enterprise solution must work with the full range of data that matters to an enterprise, including multiple structured sources with diverse schemas, like the vehicle warehouse and quality touch point application data; including unstructured data like the long-form text descriptions in the warranty claims; regardless of whether the data is inside the company, like the warehouse, or outside the company like the NHTSA claims or JD Power data.
It delivers in-memory performance, but is not memory bound. An enterprise solution must maintain fully interactive query response times even when the data is too big to fit in memory. Endeca realized this years ago when it combined search and browsing in eCommerce because search indices are often too big to fit in memory. Oracle EID is written for multi-core, multi-processor servers and uses proprietary optimization algorithms to exploit the full memory hierarchy from on-CPU cache all the way down to disk.  It is a solution for provisioning targeted discovery apps. It provides IT with a new capability to quickly deliver discovery apps wherever the business needs them. 

Over time, we will see strong adoption of Data Discovery applications that further compliment and augment Business Intelligence solutions and why we will continue to see polyglot analytics take hold. 

Friday Apr 06, 2012

Does your analytic solution tell you what questions to ask?

Analytic solutions exist to answer business questions. Conventional wisdom holds that if you can answer business questions quickly and accurately, you can take better business decisions and therefore achieve better business results and outperform the competition. Most business questions are well understood (read structured) so they are relatively easy to ask and answer. Questions like what were the revenues, cost of goods sold, margins, which regions and products outperformed/underperformed are relatively well understood and as a result most analytics solutions are well equipped to answer such questions.
Things get really interesting when you are looking for answers but you don’t know what questions to ask in the first place? That’s like an explorer looking to make new discoveries by exploration. An example of this scenario is the Center of Disease Control (CDC) in United States trying to find the vaccine for the latest strand of the swine flu virus. The researchers at CDC may try hundreds of options before finally discovering the vaccine. The exploration process is inherently messy and complex. The process is fraught with false starts, one question or a hunch leading to another and the final result may look entirely different from what was envisioned in the beginning. Speed and flexibility is the key; speed so the hundreds of possible options can be explored quickly and flexibility because almost everything about the problem, solutions and the process is unknown. 
Come to think of it, most organizations operate in an increasingly unknown or uncertain environment. Business Leaders have to take decisions based on a largely unknown view of the future. And since the value proposition of analytic solutions is to help the business leaders take better business decisions, for best results, consider adding information exploration and discovery capabilities to your analytic solution. Such exploratory analysis capabilities will help the business leaders perform even better by empowering them to refine their hunches, ask better questions and take better decisions. That’s your analytic system not only answering the questions but also suggesting what questions to ask in the first place.
Today, most leading analytic software vendors offer exploratory analysis products as part of their analytic solutions offerings. So, what characteristics should be top of mind while evaluating the various solutions? The answer is quite simply the same characteristics that are essential for exploration and analysis – speed & flexibility. Speed is required because the system inherently has to be agile to handle hundreds of different scenarios with large volumes of data across large user populations. Exploration happens at the speed of thought so make sure that you system is capable of operating at speed of thought. Flexibility is required because the exploration process from start to finish is full of unknowns; unknown questions, answers and hunches. So, make sure that the system is capable of managing and exploring all relevant data – structured or unstructured like databases, enterprise applications, tweets, social media updates, documents, texts, emails etc. and provides flexible Google like user interface to quickly explore all relevant data.
Getting Started
You can help business leaders become “Decision Masters” by augmenting your analytic solution with information discovery capabilities. For best results make sure that the solution you choose is enterprise class and allows advanced, yet intuitive, exploration and analysis of complex and varied data including structured, semi-structured and unstructured data.  You can learn more about Oracle’s exploratory analysis solutions by clicking here.
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