Best Practices

Big Data Scientist / shutterstock

Yesterday we examined the skillset of a Big Data Analyst; today, let's take a look at what a good Big Data Scientist (aka "the sexiest job in the 21st century") has to be capable of doing. However, be forewarned: perhaps only a handful of big data scientists will have all skills as mentioned here.[read more]

Big Data analyst / shutterstock

A big data analyst needs to be able to support the business and management with clear and insightful analyses on the data at hand. This includes data mining skills, advanced modelling techniques, testing and creating and explaining results in clear and concise reports.[read more]

perception gap

Consumers believe Sears is just for tools and electronics; is this the perception Sears wants to portray? What is Kroger doing better than others are? Walmart tweets way more frequently than other brands, and consumers reciprocate. 4 brands, 1 week and 100,000 Tweets: this infographic lays it all out for you.[read more]

data archive / shutterstock

Preserving knowledge for generations is no easy task. Key components of this massive undertaking include decisions in technology, architecture, data storage, and data accessibility. What are steps to architect a solution to keep your own data safeguarded and accessible long-term?[read more]

stock market genius / shutterstock

The way Buffett operates is not unlike the best use cases for big data. Among other things, his success lies in his ability to make good decisions in accordance with quality benchmarks. This is the key to using big data well, and to business success in general.[read more]

spreadsheet / shutterstock

Data management professionals have long and sometimes rather quixotically driven organizations to “get past the spreadsheet culture.” Maybe that’s misguided. The recent furor over a widely read paper may show how we can look to scientific peer review for a way to govern data, spreadsheets and all.[read more]

big data debate / shutterstock

Whether you use small or big data, your imagination (developing theories) and integrity (following the scientific method) are what counts. There is nothing wrong with a scientific mind-set based on empirical observations, as long as people don’t see cause-and-effect in correlations.[read more]

IT disaster plan / shutterstock

When considering business continuity and disaster recovery options, there’s really only one constant from business to business: it’s important to have a plan. If something happens and there isn’t a plan, your company may never be able to get back on its feet again. But where do you start?[read more]

big data & healthcare

With so much waste and opportunity in the healthcare industry, it should be no surprise that quite a few software vendors are focusing on Big Data–and not just behemoths like IBM. Start-ups like Explorys, Humedica, Apixio, and scores of others have entered the space.[read more]

A new analytic architecture

Gartner recently published a new research note called ‘Market Trends: The Collision of Data Discovery and Business Intelligence Will Cause Destruction.’ (Data discovery is Gartner’s term for Business Discovery.) The Gartner report sets out two possible scenarios.[read more]

Predictive analytics whiz: Dr. Eric Siegel

In this interview, Social Media Today's Henry Spethmann speaks with Dr. Eric Siegel -- author of the new book "Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die" -- about what predictive analytics is and how it can be applied to a number of different disciplines.[read more]

data flow

With big data come a few challenges. What can we do when data flows faster than it can be processed? There is a solution that benefits everyone (users, companies such as Google, Amazon, Netflix, Facebook or Twitter, and clients): better use of data science.[read more]

Data analysis team

Ron Johnson, the retail superstar behind the Apple store and Target’s turnaround, was hired to bring Penney back to profitability—and failed. It should be a lesson for us all. Company leaders—CEOs and boards—should hold decision-makers accountable for making data driven decisions.[read more]

Big Data privacy / shutterstock

Technological progress has always led to heated debates about the threats a new technology would pose for society and humanity. Entering the era of big data, the fear is loss of privacy. There are three different parties we can look at in taking care of that: Governments, Organisations and Consumers.[read more]

Bad data

What keeps IT guys up at night? All that bad data their bosses are using to run the business. By establishing these processes, IT departments can cut the business data deluge to a manageable flow of good information, ensuring that the decision-makers downstream aren’t using two wrongs to make a bad insight.[read more]