Digitalization and the rapid technological development have resulted in an abundance of data across industries, and this volume is only expected to increase.
To extract insights from “big data” – data sets that are too large or complex for traditional data processing technologies – organizations need sheer processing power, raw storage, and strong data analytics capabilities.
Whether your organization is already neck deep into big data technologies or thinking about exploring the space, it’s best to get to know the landscape first in order to set clear goals and evolve strategies.
The big data & analytics landscape: 10 facts you need to know
Emerging digital infrastructure, technologies, and habits are contributing to the ever-increasing data volume. By the end of this year, the total amount of data in the world is forecasted to reach 59 zettabytes. To illustrate, one zettabyte is approximately equal to a billion terabytes.
2. Stored data is doubling every 4 years.
With the growing data volume comes an increasing demand for data storage. The worldwide installed base of storage capacity, which IDC dubs the “Global StorageSphere” is expected to grow nearly 17% this year—a total of 6.8 zettabytes.
This stems from the fact that 75% of organizations will shift from piloting to operationalizing or deploying artificial intelligence by 2024. Advanced analytics solutions have shown to provide vital insights and solutions for organizations, and utilization will only increase in the coming years.
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Speaking of growing usage, enterprises will continue to rely on big data and analytics providers, resulting in tremendous market growth forecasts. The largest share of revenue (39%) in 2019 comes from services spending, and this trend is expected to continue.
5. 35% of large organizations will participate in formal online data marketplaces by 2022.
The increasing growth of data is a testament to how valuable it is to organizations across industries. It’s not surprising then that a formal online data marketplace is expected to crop up in the next few years, with a fraction of large organizations acting as sellers or buyers.
6. 53.7% of c-level executives consider transformation to be the principle driver of AI and big data investments.
This holds particularly true for the financial and healthcare services industry, sectors that not only deal with massive amounts of data, but also volatility and constant regulation. Digital transformation in these spaces will be one of the main reasons organizations will invest in big data technologies.
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Majority of data is unstructured—in the form of audio, video, images, and text. Sophisticated data analytics tools such as text and sentiment analysis, pattern recognition, and speech-to-text conversion are required to extract insights from this type of data. Enterprises have yet to fully integrate these technologies.
Similarly, majority of data available in organizations remain underutilized. After all, the process of converting raw data into actionable and valuable insights is easier said than done. Not only do organizations need to invest in analytics technologies but also a data-driven culture that’s present across departments.
Despite the increasing data volume and the numerous opportunities presented by this growth, only a handful of organizations are operationalizing big data in multiple functional cases.
On a positive note, big data is becoming an important topic on the agenda of executives. Organizations who have not yet adopted the technology are expressing interest in future uses. In fact, a 2019 report shows that big data analytics ranks 26th in a list of 37 technologies vital to business intelligence.
Related: Big data in the telecommunications industry
From big data to intelligence
These figures only highlight the pressing need of data analytics technology. A massive wealth of data requires a strong analytics foundation. By turning big data into valuable insights, your organization can gain confidence amid volatility, deliver relevant products and services, and overall make informed decisions.