On an unassuming spring morning, I walked out to check my mail and saw a coupon in my mailbox of an energy drink that appeared in my dream on three consecutive nights.The coupon also came with a personal note: “We are offering this to you because we know you were dreaming about this on 8th, 9th and 10th of October by around 2:39 a.m. Sounds scary? But not too farfetched. Someday, our savvy marketers will call this “Dream Analytics.”
- The Harvard Business Review, a noted authority has declared “Data Scientist“ to be the sexiest career of the 21st century
- A McKinsey Report says by 2018 there will be a shortage of 140,000 to 190,000 people with deep analytical skills
- “Data scientist” may soon replace “lawyer” or “doctor” as the profession of choice for parents that encourage their children to pursue successful careers
In almost all of my discussions, some of the common terms used that often are Data Quality, Completeness and Accuracy (and many other for sure). However, we don’t talk much about Trust! Can I trust the data so that I can blindly go ahead with my business critical decisions? It could be that it is taken for granted or all of us implicitly assume (rather pretend to assume) that if somebody addresses the quality, completeness and accuracy – that Data can be trusted.
How are some (many) organizations approaching the Big Data run? This came up in an interesting conversation with one of my friends (who is a Big Data Entrepreneur as well).
I am sure all of us agree that the traditional data warehousing itself took a long time to get matured in terms of the processes and governance aspects. I still don’t know if it is matured enough yet. Many of the traditional warehouses have been built over a period of time (with most of them starting small and enhancing it over the years) and because of the very reason, it’s getting more complex and difficult to manage.
I happened to read a report (named- Analytics: The real-world use of big data) on a study conducted by “The IBM Institute for Business Value” and the “Saïd Business School at the University of Oxford”.
One interesting finding which made me write this note is – relatively small impact of social media data on the current big data marketplace. A lot of the discussion about Big Data in the media is focused on social media data and how it could be leveraged, how social media could be used for customer engagement and so on- the reality coming out from this survey was – only 7 % of respondents defined big data that way.
Big Data is only good if you have the ability to use it. With all the technology advancements, it is not really a challenge to get and store huge amount of data- be it be structured or unstructured- But what next? It is easy to get carried away with all what is being discussed about big data. When you are embarking on a big data initiative, first bring clarity on “What business problem are you trying to solve”. Solidify that thought by mapping this to your organizational objectives.