While Datameer has been focusing on continuing to deliver end-to-end business intelligence platform on Hadoop, there's been a lot of increased interest in (big) data analytics in the rest of the world. This both validates the market potential and creates challenges for other business aspects. Let's take a look at a few examples:
1). Analytics is dubbed by Inc magazine as one of five most competitive areas for talent, which means data analyst and data scientist roles will continue to be some of the hardest jobs to fill in 2012
Analytics is the science of analysis, and it is the application of computer technology, operational research, and statistics to solve problems in business and industry.
As data becomes more accessible, more decisions are made with insights from the data. "Analytics is becoming a central hub across companies where everything (web, marketing, sales, operations) is being measured and each decision is supported by data."
Analytics professionals are in higher demand than ever: Monica Rogati, a founding member of the data science team at LinkedIn, shared at the Strata Conference a graph of analytics and data science job growth, that is exponential in nature, even when properly normalized.
2). Enterprises are putting more emphasis on data analytics, as they seek to better understand their customers' behaviors.
The benefits are easy to see: “Data analysis will drive Intel's future", "EBay acquires data analysis firm Hunch to boost recommendations", "Visa Europe invests in Beyond Analysis for data analytics". Intel, EBay, Visa, and other companies sit on massive data sets, which can be a very rich source for them to better understand patterns and behaviors, and serve as a basis for predictive analysis.
Companies are working on creating a more intuitive and pleasant user and customer experience, which means they must effectively correlate purchasing and consumption patterns (often structured data) and sentiments around the purchases such as social media comments and response to certain interfaces (often unstructured data).
"Analyzing the sheer volume of transactional data is no small task. It could be very easy to get lost and drown in it all" says an EBay executive. Analyzing unstructured behavior to understand and predict behavior is even more challenging.
3). The significance of analytics is showing up more in entertainment and politics, signifying increased popularity as well as the introduction of the field to the general public.
*CNN’s article “How Obama's data-crunching prowess may get him re-elected”
discusses how the Obama campaign is taking data analytics seriously, as predictive modeling/data mining and data-crunching may not just give an edge, but may make the winning difference in a tight race. With 23 million Facebook likes, and 10 million twitter followers, the Obama data crew may know and learn a lot about these “fans”, cater to them, and win their votes.
*In the movie Moneyball, Oakland Athletics GM Billy Beane turned the baseball industry upside down by “using objectivity and data to help pick a baseball team” rather than trusting on gut feels of “experts”. Beane was able to manage the Oakland As to accomplish 5th best regular-season record with player salaries at 24th of 30, using sabermetric principles to run the team cost-effectively.
*The CBS series “Person of Interest” where an ex-CIA hitman partners with a scientist to prevent crimes before they occur by collecting and analyzing data. Unlike the previous two examples, which are from or based on real life, this series exposes the importance of data analytics to solving crimes to the general audience.
What these have in common is data and analytics are becoming popular with non-traditional high-tech, finance, retail industries, as people find easier ways to correlate different types of data, whether structured and unstructured. In doing so, they can answer important and interesting questions that they could not have before to solve real problems: what algorithms can I use to find the best talent? Has there been a rogue trader in house? Which store should be closed and which should be expanded to achieve the best revenue?
These three examples feed off of each other: as more emphasis on analytics drives a higher demand of talent in that field, more activities take place in the media, entertainment, and even politics.
Being able to perform data analytics is one thing, successfully implementing analytics-based strategies is another. I learned from “Money ball” that: 1). Billy Beane and Peter Brand's carefully laid out strategy didn't work when not executed by Art Howe, the Oakland field manager, so Billy had to eliminate some possibilities for Art by trading some players away to "force" Art to follow the strategy on the field. 2). Data analytics and statistics didn't help in finding the help needed and aligning incentives: analytics can detect trends in historic information, but is limited when looking at team dynamics in terms of the team's "state" when winning and when losing.
Luckily as data is collected for the implementation stage, there would be an opportunity to use analytics to identify the issues, and form a solution for the new problem. I consider the examples above indicators that data analytics are getting "even bigger, hotter in 2012", and companies better be armed with the right tool to face this reality… and yes, Datameer can help.
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