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8 reasons you'll do big data this year

Andrew C. Oliver | June 30, 2016
To know what people are really doing with big data technology, you need to get dirty in the trenches. Here's what we've found

Over the past 12 months, I've been digging in the data trenches. OK, mostly I've been sitting next to the smarter people digging through the trenches and oversimplifying what they were doing in reports to management.

Very few IT projects are truly unique -- and the ones that sound unique often fall into relatively predictable buckets. Lucky for you, I've decided to come up for air and share the top eight types of projects I've seen over the past 12 months.

1. Exploring the life of a deal

Companies that do e-commerce take for granted that you can hook up a few tools and know the close rate of users coming to the website, from sales to payment. But many companies deal with a lot more data sets than Web-to-close. Mainly those data sets originate from distributors and resellers.

Each distributor or reseller presents a different data set in a different format. Sure, fundamentally, this is a core ETL/data consolidation project with BI/visualization on the front end. But for many companies, truly understanding the life of the deal (from inception to close and ongoing) is more difficult than you think. You need to combine a lot of CRM, Web analytics, and finance to say, "Yes, PPC yielded closings, but 40 percent of those customers defaulted on the first bill, so ..." 

2. Big Brother is watching and would like to offer you a latte

Companies like to know what you're doing (credit for this headline goes to a co-worker who shall remain anonymous) and sell you an item based on that activity. Your telemetry data, for example, might indicate that you've installed an app and the company knows where you are in the mall. A huge amount of big data horsepower goes into predicting what you might want to buy at any given moment.

3. Measuring the effectiveness of marketing

Marketing people do "things," and they want to know what those things were and how they relate to their KPIs. This is again fundamentally a BI project and often involves a fair amount of change data capture (CDC) and ETL or data consolidation. The actual KPIs they measure varies a lot. Sometimes these involve cubes in tools like Kylin or Greenplum. Other times these cross over into the next category: social media.

4. Taking the temperature of social media

People are talking ... a lot. Sometimes they talk about you (or, rather, your company), often in a public or semipublic social network. A lot can be learned from this, such as: How do people feel about your brand? Are your marketing efforts working? If the USGS can detect earthquakes and their magnitude from Twitter, then certainly you can learn whether your new ad campaign caused a stir or fell flat. For some industry verticals, this data capture goes well beyond Twitter and Facebook, thanks to specialized social networks.

 

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