With the always-evolving digital transformation, organizations have been hard-handed to keep up with the digital disruption. In recent years, as businesses have started to realize the potential of data towards development and productivity, a paradigm shift has taken place in the way data was being used and managed.
Gone are the days when ‘data’ was just stored in repositories and archives for future references; rather today it is analyzed exhaustively to shape the future; furthermore to predict the future.
“By 2023, data literacy will become an explicit and necessary driver of business value, demonstrated by its formal inclusion in over 80% of data and analytics strategies and change management programs. —Gartner: Our Top Data and Analytics Predicts for 2019”
So, what does Big Data have for the future? Let’s pitch in to figure out the horizons with Big Data.
#1. Data Governance is Inevitable
Voluminous data is produced every single day. Particularly with the development of mobile devices and IoT, a minimum of 2.5 quintillion bytes of data is generated today; and studies state this will continue exponentially.
“By 2025, there would be a big and tremendous volume of data collections, and that would be nearly 163 zettabytes (Nearly 163 trillion GB). – Bibrainia Data Confessor”
With this rate of data growth, data governance is inevitable. Forrester Research states that only 26% of European companies are compliant with GDPR. Effective management of data will be necessary not only to maintain data quality, and accessibility but also to disrupt the digital era successfully.
#2. AI, Machine Learning and NLP – a new upgrade for Big Data implementation
Handling the exponential data growth and producing prompt insights has been an all-time challenge for Big Data; especially for scenarios such as consumer behavior prediction, market dynamics and video analytics for fraud detection. However the development of AI, ML and NLP can help overpower this Big Data challenge by enabling real-time insights with contextual intelligence. Gartner’s studies state that cognitive intelligence and ML will be an essential element for predictive analysis in the future.
“Spending on AI and ML will rise from $12 billion in 2017 to $57.6 billion in 2021” – IDC.
#3. Check out Data as a Service
With the significant amount of data produced just by smart mobile devices, the future will be a place where Data will be delivered as a service just like PaaS and SaaS, to enhance data agility; and organizations will be optimizing their purchase decisions of various algorithms to be bought instead of programs. Some leading vendors of DaaS are MuleSoft, Oracle, Microsoft.
“By 2020, 90% of large enterprises will be generating revenue from data-as-a-service. —IDC FutureScape: Worldwide IT Industry 2018 Predictions”
#4. CDO – the new industry standard to measure an organization’s data integrity
A huge demand will arise for Data scientists and Data analysts who can deal with gigantic data projects and account for the integrity and validity of data. As per IBM, the demand for advanced analysts and data scientists will grow by 28% by the year 2020.
A CDO (Chief Data Officer) would in the same vein as the CEO, COO, CIO, CXO or CFO accounting to an organization’s data integrity and validity.
#5. Edge analytics with real-time data is the new benchmark for Data Analytics
“By 2022, more than half of major new business systems will incorporate continuous intelligence that uses real-time context data to improve decisions. —Gartner: Our Top Data and Analytics Predicts for 2019 “
Organizations will be more focused on predicting with real-time data rather than analyzing the historical data. They won’t be waiting to collect transformed or raw data to reach centralized data centers or warehouses to analyze; instead, they would be crafting edge analytics frameworks that capture real-time data from networks and smart mobile devices, to transform them into actionable data.
#6. Dark Data will be a part of a Big Data Checklist
To make the most of Data crunching it is imperative to operate on all types of data. For this reason, dark data will be added to the data analytics checklist, as today, slowly organizations have started to realize the hidden value that dark data possess. Referring to the untapped data that is already available in an organization’s repository, an IBM study states that by 2020 more than 93% of all data will fall under Dark Data
#7. Privacy will be harder than ever before
With Data growing in light’s speed every single day and organization’s focusing on managing the voluminous data to get the most of it as well as providing it as an asset (DaaS), privacy will be very much at stake; and may lead to complex cybersecurity issues; Consider, Equifax data breach. Hence, organizations should prepare a robust data governance plan to address such scenarios.
Perhaps, today organizations are not able to implement Big Data efficiently. But, in the upcoming years, when organizations would be focusing on fast data and real-time decision making for businesses to impact productivity; the digital era will once again be refashioned with the fusion of big data with AI.
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