How to make better use of analytics
Speed and software capabilities are driving widespread use of Big Data. Gartner Inc. estimates that Big Data will drive some $34 billion of information technology spending in 2013. But a recent study conducted by InformationWeek reported that just 9 percent of their respondents said that their organizations fully understood the implications of big data. And 4 percent of them admitted that they hadn’t a clue.
And when asked about the biggest impediments to information management success, 58 percent cited accessing relevant, timely or reliable data, and 48 percent cite integrating data, according to the 517 information management-involved business technology professionals in our InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey.
Michael Healey, president of Yeoman Technology Group, an engineering and research firm identifies six steps to better analysis
Audit your data analysis tools: Build a complete list of the systems in use across the company; only then can you identify gaps. Don’t skip this step, even though everyone hates inventories. It’s likely there are products in use that you have no idea were even purchased. Problems arise less from a lack of tools than from how they’re configured and what data sources they pull from. For example, the marketing team may focus their entire product and behaviour data gathering on the Web — page views, orders, customer chatter — and completely miss back-end factors that can change behaviour, like availability and lead times. That’s likely easy stuff for IT to integrate into data analysis by connecting to the ERP warehouse.
Open the warehouse doors: One of the most regular feature is the hard line drawn between data stored in the conventional warehouse (usually ERP and transactional data) and information available from the cloud (normally Web and social data or input from external data sources like Web analytics, CRM systems and email data stores).You can blame this division on storage limitations or security concerns if you want, but those are both cop-outs. A cloud-based visualization tool like Chartio, Google Big Query or Domo will pull from multiple data sources that you define. Everything doesn’t have to move from the warehouse to the cloud to give the business a unified view.
Fill the gaps: Smaller IT shops rarely have a complete suite of data visualization options. In contrast, big companies using suites from the likes of IBM, Oracle and SAP, have seen those products gain advanced features that will likely meet most needs. Either way, assess how you’ll create productive visualization aids for big data, including heat maps, geospatial maps, storylines and timelines, and relationship graphs and charts. And set the bar high when evaluating toolsets: If a potential suite doesn’t support dynamic updates, visual querying or the ability to tie alerts to specific events, keep looking. There are plenty that do.
Create sample data visualization options: This is where the fun starts. Rather than just say, “Use this,” it is recommended pulling together some reference sets. Not only does that open the discussion of what’s possible, it does so in the proper way — with accurate data sets, statistical notations and some quality checks. However, don’t stop with visualization tools.
Assemble a big data action squad: A bold option for CIOs is to offer up a “rapid response” team for advanced visualization. Right now, major reports and presentations likely bounce around departments and end up in a graphics or marketing department to pretty up. Fielding an IT team with these skills will not only relieve the pressure on marketing, it will build up your portfolio of visualization scenarios and nurture employees who show an aptitude for these pricey skills. Also it is crucial to cultivate big data analytics expertise in house because these people know your business.
Stick your head in the lion’s mouth: Now that you’ve reviewed options, built up toolsets and assembled teams, we dare you to take a risk. Get 15 minutes with the CEO and ask a simple question: “What information do you want that you’re not getting now?” You may not gain that type of clarity from the exercise, but at least you’ll have some new questions to answer, and that’s a good start.
- Adobe, Microsoft, SAP Team Up For Open Data Initiative
- Millennials and Cybersecurity: Understanding the Value of Personal Data
- AI Is Making BI Smarter
- Microsoft, DSCI Team Up To Fill The Women In Cybersecurity Gap
- Applying A Customer-Centric' Formula For Business Success
- Cloud Is Critical For Driving Semicon Industry's Growth
- How Tech Is Helping Rethink Customer Engagement
- Key Technologies Redefining Human Resources
- Study Shows Digital Trust Gap Between Companies And Consumers
- Oracle To Showcase Its SaaS Innovation With AI In India