According to NASSCOM, India has the second largest internet user base globally; a figure we continue to see accelerate post the pandemic’s peak as consumers continue to move online and small businesses digitise. As of June 2020, India had an internet subscriber base of 749.1 million, which is expected to cross 1 billion by 2025. This has led to an increase in the amount of data generated and consumed. In 2019, Indians consumed the highest amount of data per month globally at ~12GB, which is expected to double over the next five years.
As data volume and variety increase and data sources proliferate, new opportunities will arise to deliver superior customer experiences, drive better business decisions and enable greater agility and resilience. New technologies and approaches – such as internet of things (IoT), cloud native development, artificial intelligence (AI), machine learning, and the modern data fabric – offer a path to this intelligent business vision.
Despite these opportunities and new approaches, businesses are struggling to manage data and generate meaningful analysis. They’re weighed down by issues such as dirty data, misaligned data collection and governance policies. These companies risk falling behind competitors, who are using data intelligence to adapt to their customers’ needs quickly and proactively. To gain actionable insights from data, one needs to address some common barriers. Let’s take a look at each of them.
#1 DATA DISCOVERY CHALLENGES
Data discovery is difficult when you have unknown data sources, poor data quality, data silos and compliance restrictions. These issues can trace their origin to data used or generated by a specific application stored in a siloed data platform, typically found in an early 2000s web application architecture or in 1990s UNIX applications.
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