As mentioned, big data analytics allows companies to tackle business problems. These problems are best understood by managers, staff and employees in the field. IT staff may not fully comprehend what is required and can provide reports that mismatches with what is needed in the field. This coupled with the correspondence time can result in managers not receiving the information in time to support their quick decision making.
By enabling staff with self-service analytics of big data, companies are empowering them to ask questions, identify problems and make informed decisions to get things right. Staff are also able to combine the data with other public information to achieve insights into market segments. Companies also free up IT resources to let them focus on more important and strategic responsibilities.
3. Visualization is key
Large data sets can contain complex information like customer profiles, purchase history, multiple touch points, geographical data, etc. This means a massive number of rows and columns if displayed on spreadsheet tools such as Excel.
Discovering insights using such a tool can be a daunting task and would take up a lot of time and effort. Users may have problems tracking a specific customer demographic across multiple spreadsheets and could potentially miss out on vital insights that can solve business problems.
A good way to address this would be to deploy a tool that allows for visual analytics. Visual analytics presents the data in simple charts and graphs, allowing users to access and view data in an easy to understand format. Using visual analytics also allows users to ask different questions and find their own answers. Today, visual analytics allow users to interact intelligently with their data, and help them to discover information by following their thought processes.
4. Plan for the future
When selecting a big data analytics tool, it is important to consider the company's existing IT infrastructure and growth plan. Needless to say, a scalable solution will allow companies to adjust accordingly - include more users when required, reduce seats when there is less requirement - when needed, saving on costs.
Another factor to consider is to invest in new and emerging database technologies. Leveraging these emerging technologies can help organizations tackle new classes of analytic problems that could not be addressed previously. Companies may want to tap on cloud computing for instance to bring benefits to a company's big data analytics capabilities because of its easy scalability, low cost.
Recently, options such as Hadoop, a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models, have also become a mainstay in the big data architecture of many companies.
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