We are all pumped about the Strata Summit next week (9/20-21) here in New York City. A.) It’s in our town, B.) one of our brightest minds was asked to speak, and C.) we are exhibiting. The theme is “the business of data,” which makes it a natural for us, and “Big Data” is all over the agenda. Double natch.
It’s an O’Reilly conference, but not for developers like most are. The presenters include thought leaders from McKinsey, the Economist, MIT Media Lab, the Guardian, Amazon, and Google; and the audience is mostly business execs of the kind that might watch the occasional TED video – our kind of folks.
There is a number of good sessions and interesting exhibitors on deck (including ours and us, of course), so here are some of the must sees, IOHO.
1010data‘s own Robert Leftkowitz, A.K.A. “r0ml” (long story) will be giving a talk on Tuesday at 10:50 a.m. entitled “Turning Their Data Into Your Money (And Vice Versa).” The talk will examine how Big Data is driving the emergence of a new business ecosystem linking data owners, analysts, and business decision makers in new and interesting ways. r0ml is one of O’Reilly’s highest rated conference speakers, so it should be a great talk.
In the 1010data demo pod, we will be showing the latest version of our cloud-based analytical platform (A.K.A. the Trillion-Row Spreadsheet™), munching on billions of rows of business data and spitting out fascinating insights with breathtaking speed. If you are a data person, your spine will tingle. If you are a businessperson, your mind might be blown.
Looking through the program, there are tons more good stuff at the show that we are also looking forward to.
Big Thinker Alert
The opening session, featuring McKinsey’s Michael Chui is titled “Big Data: The Next Frontier” and follows up on the great recent landmark Big Data study by McKinsey Global Institute by looking at “data innovation, challenges and competitive advantages.”
Attention, Sports Quants
One such recent competitive data innovation is the use of analytics in professional sports. It was the subject the very witty Michael Lewis book Moneyball and the eponymous Brad Pitt movie premiering next week. The Tuesday afternoon keynoter Paul DePodesta is one of the actual Moneyball guys. He’s a Cum Laude Harvard economics grad that, with Billy Beane, (Brad Pitt), pioneered the use of statistical analysis in baseball scouting, team management, and, most importantly, winning games. His talk will show a riveting example of a team gaining competitive advantage through data analytics.
Big Data Lessons Learned
If you don’t ask a good question, you won’t get a good answer, of course. But, how do business analysts know if they are asking the right questions? Not so obvious. Monica Rogati of LinkedIn is giving what should be an enlightening talk on this topic entitled, “Lies, Damned Lies, and the Data Scientist.” She will discuss some of lessons learned about how to carefully ask Big Data questions.
Big Data, like much of IT, is constantly changing. As the colossal volume of data continues to grow, companies are sprouting up to harness it with innovation. One such company, PeopleBrowsr is using Big Data to take on Nielsen. It’s founder, Jodee Rich, is giving an interesting talk on how they are doing it.
There will also be a number of compelling Big Data analytics company presenting and attending the summit as part of the Startup Launchpad.
Overall, it shapes up to be an incredible event. Whether you are a CIO of a company beginning to learn about Big Data or an executive who has been discussing data equity for years, we hope to see you at the Strata Summit.
Don’t forget to stop by and listen to r0ml at 10:50 on Tuesday, as well as come to our exhibit, booth number 14, and say hi.
There was a great article in the Economist about the challenges and opportunities of big data entitled Building with Big Data; The Data Revolution is Changing the Landscape of Business. The article describes the growth in various types of data, and cites a McKinsey study on the potential enterprise value to be gained by better understanding that data:
Last year people stored enough data to fill 60,000 Libraries of Congress. The world’s 4 billion mobile-phone users (12% of whom own smartphones) have turned themselves into data-streams. YouTube claims to receive 24 hours of video every minute. Manufacturers have embedded 30m sensors into their products, converting mute bits of metal into data-generating nodes in the internet of things. The number of smartphones is increasing by 20% a year and the number of sensors by 30%.
Clearly the amount of data businesses deal with every day is exploding. The article continues…
In a suitably fact-packed new report, “Big data: the next frontier for innovation, competition and productivity”, [McKinsey] argues that data are becoming a factor of production, like physical or human capital. Companies that can harness big data will trample data-incompetents. Data equity, to coin a phrase, will become as important as brand equity. MGI insists that this is not just idle futurology: businesses are already adapting to big data.
We agree with this assessment, and believe that companies need to use their rapidly expanding data to create data equity. It’s not enough just to have the data stored in legacy systems or remote silos- you must have easy access to the data and the analytic tools necessary to leverage that data to create real value. We have been speaking and blogging about related topics, like data monetization (see this recent post).
Our own VP of Marketing Tim Negris will be speaking about creating data equity through big data analysis at the Cloud Computing Expo in New York this week: Collaborative Big Data Analytics: It takes a Cloud. If you are attending the show, we invite you to come listen to Tim or stop by our booth to learn more.
Just how much data is big data? What does cloud computing really mean? How is this different than SQL? Oracle? Can you do analytics? A whirlwind of questions can be asked of many “big data” companies. Companies that help others manage large volumes of data have long had trouble describing what they truly are. This is partly because the range of solutions offered is immense. These solutions fall into two main categories.
First, data warehousing companies help companies deal with data overload. The companies may have recognized they wanted to keep their data, but couldn’t manage it themselves. They choose to buy hardware or occasionally a cloud offering to collect and maintain historical data. This offering often allows for simple analytical queries like indexing and basic aggregations. However, they lack analytic power, and either need to do pre-aggregating and indexing before each complex query or split the data set into smaller segments for analysis.
Second, there are analytic offerings. These include Excel, and for the more technical, SQL. While Excel is very flexible, it is hampered by its inability to work on large data sets and relative lack of power. SQL has relatively strong analytic capabilities, but forces data to be stored relationally. This makes the data take up much more space than it needs to, and makes many types of queries, especially time series, very sluggish on large data sets.
Companies are struggling to use these solutions to solve their problems. It’s important to consider that the biggest concern of most customers is how to leverage data to drive business decisions. The proper solution tackles this problem by providing robust analytic flexibility and power enabling both technical and non-technical decisions makers to drive strategic vision and change. This requires an incredibly fast big data platform that combines the flexibility and simplicity of Excel with the ability to do even more powerful analytics than SQL.
To truly meet our customers’ goals we have created a Big Data Analytics Platform (BigDap). We can take all the data any customer could throw at us (big data), and empower users to do lightning-fast and powerful analyses that drive business results (analytics). Perhaps most importantly, we offer non-technical end users a flexible spreadsheet like, web browser interface as intuitive as Excel, and technical users an incredibly powerful XML based query language accessible via several programmatic interfaces such as APIs, ODBC, MS Excel Add-in, and an SDK that supports most modern programming languages, all delivered securely via a managed cloud. (platform).
Using the managed cloud means that users can access the data and analytic power securely from any web browser. This ensures that there is exactly one version of the truth, and everyone working together will see the same data at the same time. It also reduces hardware costs and lets the company focus on their business needs, not how to store data.
BigDap is more than just a way to manage your data. It is more than an on demand tool to analyze some of it. This is a Big Data Analytics Platform: let your data lead the way!