Trends in analytics

4 major trends in analytics that will drive Digital Transformation

Analytics has grown tremendously in scope and scale over the past twenty years. However, we are still seeing only the tip of the iceberg. With the continued explosion in data and rapid advancements in technology, multiple advancements are happening in analytics, which will take its impact to a totally different level, making it an even more effective enabler for enterprise digital transformation journeys.

Here are the 4 trends that can significantly raise the impact of analytics on businesses

  1. Prescriptive analytics. Analytics has progressed from descriptive (what happened) to predictive (what will likely happen) to prescriptive (what should be done). This progresses analytics from insight to action, and from the realm of a support capability to a front-line capability. Machine learning is a key enabler in this progression of analytics from insight to action.

2. Continuous analytics. One of the biggest trends in data has been the explosion of real-time data. This is moving analytics from batch mode’, where analysis was done offline, to continuous analytics and insights. This trend is mainstream in both consumer and industrial situations. IT is a significant driver of this trend; it can produce millions of real-time signals enabling dynamic tracking and optimization.

3. Augmented analytics. This is about combining analytics with Al and machine learning and automating tasks that might be traditionally done by a data scientist or a specialist analytics professional. One of the biggest leverages of augmented analytics is the improvement of data quality. Often, more than 80 per cent of time and costs expended on analytics projects goes into ensuring adequate data quality. AI and ML can play an important role in improving data quality, which can significantly improve both the effectiveness and efficiency of the analytics process.

4. Cloud-based analytics. Cloud is one of the biggest technology trends of our times and I believe it will have a profound impact on how analytics is done. Cloud platforms, of course, provide a scalable infrastructure for computing that can support and enable big data and real-time analytics. More than that, cloud platforms can help streamline the process of gathering, synthesizing and processing data. This can be a major productivity booster. Additionally, cloud providers like AWS, GCP and Azure are making tremendous strides in the capabilities of their analytics platforms. Many of the tasks historically done by the analytics specialist are in-built in these platforms. This is a fascinating development and will have far-reaching implications for analytics specialists, in terms of the roles and skills required of them.


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