In current period, companies have been required to re-examine their data management strategies to create the most of the cosmic troves of data both structured and unstructured at their removal. Many have implement data infrastructure solutions to process terabytes of data that now course from first to last multiple channels. This approach is compulsory as it is becoming clear that data can give up invaluable insights to drive key business decisions. Some of the trends and strategies so as to we have seen open out over the last few years are likely to strengthen in the months ahead. A few of these include:
1) The drive to digitize: Digitization lies at the core of dealing data architecture today. Without whole digitization, companies will experience gaps in different parts of their frameworks and get sub-optimal results from data analytics. Companies that have been seeking to go completely digital when it comes to their processes will be more annoyed than ever to go after this goal.
2) Juxtaposing data insights with industry knowledge: In focusing far on data solutions and the insights they give up, companies and their leaders run the risk of ignoring their own insight and knowledge as regards the business and the industry. Data analysis without the right related considerations can result in flawed numbers or insights. For example, Google’s Flu Trends a prediction system that Google has been running in the U.S. has been termed a case of ‘Big Data hubris’ by overestimating the number of influenza cases in the U.S. for 100 out of 108 weeks.
3)Mapping internal and exterior sources: In current times, the biggest transfer in business mindset with view to data lies in the respect by companies that data from internal systems ERP, CRM, and is not sufficient. Companies seeking insights on a wide range of business and market variables have to look beyond data generated by internal processes and transactions. An successful data management strategy needs to combine internal data with those from external sources such as social media and syndicated channels. And since the data from these sources comes in variable formats text, numerical, graphical companies have to have a flexible and versatile framework to contain and process these
4) increasing demand for visualization: Companies are experiencing a daily torrent of data that desires to be processed instantly for it to be functional. In this environment, users need entrance to instant and real-time analytics but in an easily interpret package. In this respect, data visualization is going to turn into more relevant and important. Data analytics is an industry agnostic function but the need for it is most evident in the e-commerce space where online marketers can leverage the results of click-through analyses and similar activities to streamline their retailing strategies. In a broader sense, however, data analytics is relevant for any company with a strong digital footprint and keen customer focus. Financial firms and banks can leverage it to tighten their risk management and fraud prevention measures. Utility companies can use their vast quantities of meter usage data to develop variable pricing plans, among other things..