According to the research firm IDC the data analytics market is about to explode. In 2016 spending on big data and analytics was around $130 billion. By 2020 that figure is projected to be $203 billion. With companies spending billions more every year, the value and utility of analytics is growing rapidly. Here are some predictions of how analytics will evolve in the coming year:
Privacy Becomes Paramount
Sweeping new data protection rules went into effect in the EU in May 2018. Those rules are likely to be matched by other global governments as privacy and data security become serious concerns. As companies begin collecting, storing, and utilizing ever larger amounts of data, ensuring that data is secure and transparent will be a priority. Companies will face huge fines and widespread public backlash if they fail to keep data safe
Customer Experience Drives Competition
Companies have traditionally competed over price, selection, service or other variables. As commerce continues to evolve, all those variables will become both more and less important. Companies will need to ace them all, but they will distinguish themselves through the quality of the customer experience. Analytics is a crucial component because it allows companies to track and then predict consumer behaviors. That leads to greater customization and seamless shopping. Near-future companies must get customers right, which means getting data right.
Analytics Gains Flexibility
Until recently the focus of analytics has been on accessibility. Dashboards are intended to make the volume of huge data sets and the complexity of data science accessible to a lay user. However, advances in technology and changes in business priorities are making flexibility more important. Dashboards typically offer limited functionality and standard sets of metrics. Embedded analytic dashboards, by contrast, deliver metrics and insights based on user queries. None of the accessibility is lost, but users can take a much deeper and self-directed dive into the data. By 2019 expect traditional dashboards to be replaced by more advanced alternatives.
Skills Gap Gets Worse
There is already a severe shortage of qualified data scientists. And this problem has led more than one analytics initiative to be delayed or discontinued. The number of graduates is growing, but the demand is growing even faster. Larger data volumes, new data initiatives, and the onslaught of IoT will all strain future analytics agendas. In response, companies will increasingly prioritize self-service analytics tools. The easier they are for average users, the less companies require in-house data expertise.
Machine Learning Aids Analytics
The focus of analytics is increasingly on boosting the technology’s basic performance with the aid of machine learning. Adaptive intelligence can learn from user behaviors and improve analytic outcomes as a result. It identifies trends and patterns in order to recognize what kind of information users really want. Over time, this leads to deeper analysis, faster results, and an overall upgrade in analytics. Therefore, it’s not surprising that machine learning will be a major feature of analytics by 2019 and beyond.
Some of these predictions are positive while others are negative. But the takeaway from all of them is the same: Effective analytics is an asset all companies require. It’s true now, and it will be certain by 2019.