By Eric Bezille-Oracle on mai 31, 2016
Since 2011 and McKinsey analysis launching the “Big Data” phenomenon and my first blog entry on this trend (here), many things evolved. It is no more a “hype”, and depending on which angle you are looking at it, “Big Data” evolution brings new jobs like Chief Data Officer, new enrichment and additional complexity for operations with the continuous evolution of tools revolving around it. Either way, there is no way to stop it if you don’t want to stay behind, or even become irrelevant. Digitalization of the World and Data are removing the previous known barriers to entry. If you are not convince yet, have a look at the valuation of AirBnB compare to AccorHotels. This is call now “Uberization”, and the word even made the French dictionary this year. All thanks to mastering Digitalization technologies and Data to offer the right services at the right time at the right price: “Data is eating the world”, and you should better be a master at it. Just getting back to my previous example about AirBnB and AccorHotels, AccorHotels is not standing still, and is investing heavily to master their Data.
Getting the right tools for the Job
Following McKinsey 2011 prediction, mastering Data starts with Data Scientists… but even here, Data Scientist Job is facing evolution (or revolution). In Jennifer Lewis Priestley's article "Data Science: The Evolution or the Extinction of Statistics?" , not only will you get an interesting view on this evolution, but I also invite you to look into the comment from Andrew Ekstrom , that I would summarized in one sentence: “get the right tools for the job, that can scale to crunch more and more data”.
And tools have evolved also pretty fast, for better enrichment and capabilities, but also bringing more additional complexity to keep up. At the end of the day, what you would like is a DataLab in a box, ready to use, with the right capabilities. Spending time building it, maintaining it, moving from Hadoop MapReduce, to Yarn, to Spark (to name a few), combining it together with NoSQL and SQL sources is complex (check Mark Rittman - Enkitec E4 Barcelona : SQL and Data Integration Futures on Hadoop presentation for more details). Would not it be nice if you can get all of this ready to use, to be focus on the analysis to get the value of ALL your Data. To take another analogy, just think if you had to build your car before using it, not really convenient. Unfortunately it is often what most of IT tends to do.
DataLab in a Box
Applying the Converged Infrastructure to Big Data, what we call a Big Data Appliance, results in the ability to provide to you a car ready to drive, encompassing not only a scalable Hadoop platform combine with NoSQL, but as well SQL connectors, with a nice and ready to use visual exploration tool (Big Data Discovery) to get the value out of your Data at the hands of Data Scientists. All in all a DataLab in a Box, available both in the Cloud or on your premises. Many of our customers are leveraging it with success (I invite you to have a look here for references and use cases). That’s why Oracle was named leader in The Forrester Wave™ for Big Data Hadoop Optimized Systems, Q2 2016.
Now that you know how to get an Operational DataLab (in a Box), where do you start from here ?
The first steps to get to the Value
The 2 tips to keep in mind from many customers having already found the value in Big Data:
- Start with the Data that you already have, by bringing them into your DataLab
- Ask the right “SMART” question, top burning issue, for your Business line to be solved
With that, you should be in the right place to accelerate your Data Value to stay ahead.
To go further:
- Data Science for Business -What You Need to Know about Data Mining and Data-Analytic Thinking- By Foster Provost, Tom Fawcett
- How to Measure Anything: Finding the Value of Intangibles in Business - by Douglas W. Hubbard
- Jennifer Lewis Priestley's article "Data Science: The Evolution or the Extinction of Statistics?" and comments
- Mark Rittman - Enkitec E4 Barcelona : SQL and Data Integration Futures on Hadoop
- The Forrester Wave™ for Big Data Hadoop Optimized Systems, Q2 2016
- Big Data Appliance
- Big Data Discovery
- Big Data SQL
- References and use cases