- Self-service will be a catalyst for a digitized economy
Before the COVID-19 pandemic, there was an increasing adoption of IT in different processes in organizations. Enterprises were planning how to improve and ensure speedy extraction of insights by investing in advanced infrastructure while guaranteeing a minimum disruption of existing business processes. The speed of modernization was accelerated, resulting in increased budgets and resources due to the pandemic. With the rise in needs and fewer resources for IT and data teams, self-service and democratization will become a main area of focus. Organizations will provide insights and means for users to resolve business issues inside departments. This means strong data governance policies will be developed to allow data access by business users while ensuring top levels of security and compliance are met.
- Augmented data management will be a new normal
The use of active metadata, machine learning, and data fabrics will increase as organizations seek to connect and automate data management tasks dynamically. This will reduce data delivery time by more than 30 percent by 2021. Artificial intelligence techniques will be used to recommend the best course of action and data governance controls. According to Gartner, data fabric is something that uses continuous analytics over the existing metadata assets that are discoverable to support the design, deployment, and use of integrated and reusable data objects irrespective of the platform or architecture.
- Invest in data transformation to improve analytics
With the upsurge in data sources and the amount of data in organizations in general, data streams seem not to be keeping up fast enough. IDG Research survey reports that organizations spend almost half of their time preparing data. They take up to a week to prepare data for a normal project. With this inefficiency, enterprises are looking for better ways to enhance data transformation processes and ensure analytics-ready insight is obtained. Most of them have shifted to the cloud to reduce the time it takes to join siloed data together, denormalize and enrich it as well as apply business logic. As pressure increases on organizations to invest more resources and raise budgets, most of them will try cloud solutions to help their data transformation efforts due to the fewer resource requirements needed to do it.
- AI will become a smarter, faster, and most sought after analytics technology
According to Gartner, over 75 percent of enterprises will shift from piloting AI to fully operationalizing it by 2024. This means that AI adoption and operationalization will increase as soon as this year. By the end of 2024, streaming data and analytics infrastructures will have gone up five times. The current challenges will be reduced, and most historical data will likely be obsolete by then. The disruptions will oversee enterprises embracing learning algorithms, reinforcement learning, and edge computing to improve data analytics and get more insights. Data analytics will help organizations find solutions and direction through its ability to ease gathering, transforming, and analyzing data.