A Quote by Gurjeet Singh
My mission is to bring the power of big data insights and analytics to every company.
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The company started in the early 90s or late 80s. We were a behavioural science company. We didn't pivot into data analytics till 2012. So, all the data that we collected pre-2012, which was done by the British company SBL group, was collected through quantitive and qualitative research on the ground.
Every company has big data in its future and every company will eventually be in the data business.
We are going to completely change what it means to do advanced analytics with our data solutions. We have machine-learning stuff that is about really bringing advanced analytics and statistical machine learning into data-science departments everywhere.
We have a long way to go to understand that web analytics is a thinking man's tool, not a solution unto itself. On the bright side, 73% of those surveyed might still figure out that web analytics can help them drive actionable insights one day.
The promoters of big data would like us to believe that behind the lines of code and vast databases lie objective and universal insights into patterns of human behavior, be it consumer spending, criminal or terrorist acts, healthy habits, or employee productivity. But many big-data evangelists avoid taking a hard look at the weaknesses.
Every company has messy data, and even the best of AI companies are not fully satisfied with their data. If you have data, it is probably a good idea to get an AI team to have a look at it and give feedback. This can develop into a positive feedback loop for both the IT and AI teams in any company.
A data scientist is that unique blend of skills that can both unlock the insights of data and tell a fantastic story via the data.
Without big data analytics, companies are blind and deaf, wandering out onto the Web like deer on a freeway.
The creative folks intuitively design what's best for the user, while data folks provide great insights. The true unicorns are those who can go end-to-end designing, building, measuring, analyzing, and iterating with a combination of user intuition and deep analytics.
Vivametrica isn't the only company vying for control of the fitness data space. There is considerable power in becoming the default standard-setter for health metrics. Any company that becomes the go-to data analysis group for brands like Fitbit and Jawbone stands to make a lot of money.
We get more data about people than any other data company gets about people, about anything - and it's not even close. We're looking at what you know, what you don't know, how you learn best. The big difference between us and other big data companies is that we're not ever marketing your data to a third party for any reason.
You look to Google, you see this incredible world of information, you see the advertising, but you also get Google Analytics. And Google Analytics coupled with Salesforce's sales and service and marketing means that both of our customers are going to have customer insights that they've never had before. That is really exciting.
If you are looking at data over and over you better be taking away valuable insight every time. If you are constantly looking at data that isn't leading to strategic action stop wasting your time and look for more Actionable Analytics.
Business analytics or predictive modelling is a $100 billion industry, and $41 billion is spent on outsourced business analytics every year. I think that's about twice the size of the movie industry - it's really big.
People think 'big data' avoids the problem of discrimination because you are dealing with big data sets, but, in fact, big data is being used for more and more precise forms of discrimination - a form of data redlining.
A great deal of creativity is about pattern recognition, and what you need to discern patterns is tons of data. Your mind collects that data by taking note of random details and anomalies easily seen every day: quirks and changes that, eventually, add up to insights.
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