What Are The Current Trends in Data Analytics?

Over the past 10 years, data has grown into a behemoth that dominates business intelligence. A huge percentage of the global population has access to the cloud. Spreadsheets have taken a backseat as actionable and insightful data visualizations and interactive business dashboards moved into the driver’s seat. Below are the Top 2 current data analytics trends to keep an eye on this 2018:

#1 Artificial Intelligence

There’s no doubt that AI and machine learning are revolutionizing the way we interact with analytics and data management. Gone are the days of passive reporting. Now, we welcome proactive analysis to see and understand what’s happening in real time. The demand for this kind of tool has increased drastically and the arrival of IoT (Internet of Things) has brought a massive amount of data to the table as well.

Statistics show that over 50% of  large global organizations will use advanced analytics and the algorithms built on them to gain leverage. And what is at the heart of those algorithms? Yes, it’s AI. AI that understands the data and can predict what’s coming. The AI’s deep learning can allow machines to operate autonomously and make decisions in the place of actual people, in many cases better than actual people, This will greatly affect business decision-making and management protocols and unleash new possibilities that we can’t even imagine as yet.

#2 Predictive and Prescriptive Analytics Tools

Predictive analytics is the practice of extracting information from existing data sets in order to predict future probabilities with an acceptable level of reliability. This process is an extension of data mining and includes estimated future data, which incorporates; error possibilities, alternative risk scenarios, and risk assessments.

In business, predictive analytics can be used to analyse current and historical data to better understand the drivers influencing customers, products, and partners. As a result, businesses that make use of predictive analytics can identify potential risks, opportunities and can develop more effective market and business strategy.

On the other hand, prescriptive analytics takes a step further into the future and examines data or content to determine the best decision that can be made at a given time and provides insight into what steps should be taken in order to achieve an intended goal. This process includes techniques such as predictive modelling, simulation, heuristics, and machine learning.

Prescriptive analytics tries to see the effects of future decisions in order to adjust those decisions accordingly before they’re actually made. This is extremely helpful for in the scheduling, production, inventory, and supply chain design processes of businesses.

Other trends to look out for in the data analytics field are:

  • Natural Language Processing
  • Deep Neural Network
  • Data Quality Management and Governance
  • The Multi-Cloud Strategy
  • Humanizing Customer Experiences
  • Autonomous Databases
  • Importance of Chief Data Officer
  • Streaming Analytics and Autonomous Business Intelligence

Collaborative Business Intelligence based on data-driven analytics has now become expected in modern businesses. Let Fusion Professionals help you move towards extracting the maximum value from these data analytics trends.

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