Advertisement

Three Ways Data Analytics Will Progress in 2022 and Beyond

By on
Read more about author Ajay Khanna.

Most industries have seen tremendous change due to the pandemic over the past two years, which has brought new and ever-evolving data that businesses need to make sense of. With that, data analytics tools have become more imperative than ever, as they can help organizations analyze changing business patterns as well as offer insightful visibility into past, present, and future performances.

In fact, according to IDC, global spending on big data and business analytics solutions will have increased by over 10% in 2021 – reaching over $215 billion. These advancements have been seen across all industries – from banking, manufacturing, and professional services (which made up 33% of big data spending in 2021) to process manufacturing, telecommunications, and government agencies (which have together spent $47 billion on big data this year). And those numbers aren’t showing any signs of slowing, especially as businesses continue to grapple with the ripple effects caused by the pandemic.

With more data being created than ever before as well as continued business disruptions caused by the pandemic, here are three trends we can expect to see in 2022, as organizations strive to leverage more analytical insights to improve business outcomes and enhance their competitive advantages. 

Enterprise-wide Data Literacy will be necessary for becoming a data-driven organization: Consumers today are accustomed to free-form search interfaces, seamless transactions via tapping a screen, and contextual, personalized information pushed out to them 24/7. This expectation goes beyond just day-to-day transactions and has revealed how analytical tools are evolving to simplify complex data analytics and increase Data Literacy. Business users want to be able to seamlessly and quickly analyze data at hand without needing to rely on data scientists and BI analysts. Organizations need tools that democratize data analysis so that every employee – even less technical ones – can make more informed and comprehensive decisions within moments. 

These tools will also show growing importance as the data scientist shortage continues. This shortage has presented organizational challenges, as existing data teams may not have the bandwidth to obtain, analyze, and report on specific data campaigns. By democratizing data analytics and implementing tools that anyone within an organization can gain access to, organizations can make up for the limited resources that they’re facing. 

Further to that point, data lakes will also become more accessible to business users, as they have traditionally been restricted to advanced data analyst teams and data scientists for machine learning. While business teams have traditionally visualized data in relational databases and cloud data warehouses, having access to data lakes will unlock the full potential of modern and robust data analytics tools, and enforce enterprise-wide Data Literacy. 

The modern data stack will continue to evolve: The adoption of the modern data stack has been driven by a number of factors – for example, the shift to the cloud, the rise of machine learning and AI, and limitless availability of storage and computer power. While organizations have traditionally focused on the storage layer of the data stack, the analytics layer will become increasingly more important in 2022. With that, companies will seek tools that enable them to analyze data directly within their preferred data warehouses or lakes, eliminating unnecessary, time-intensive data prep and transformation to get faster, better insights.

Alongside the ever-evolving data stack, we’ll also see the convergence of data warehouses and data lakes in 2022 so that organizations can benefit from managing their data assets in one place. The benefits of this convergence are twofold. First, it supports enterprise-wide Data Literacy as business teams gain access to data lakes for more advanced and efficient analysis. Second, it prompts analytics providers to work with both sides to improve end-user capabilities, which is particularly important as enterprises continue to shift from on-premise data to cloud data warehouse-centric architectures. 

Organizations will adopt more hub-and-spoke models: In 2021, many organizations reconfigured their office structure to adapt to the pandemic’s impact on work environments. Some had employees come back to the office in person while others opted to stay completely remote or they adopted a hybrid, hub-and-spoke model. 

This hub-and-spoke model is also applicable to data infrastructure, and we’ll see more of these models emerge in 2022. By adopting a hub-and-spoke model, IT teams can strengthen their stronghold to centralize data but also enable decentralized analytics teams to work off governed data and metrics for a wide variety of use cases. The benefit is that data can be stored in one centralized location, but also be accessible to everyone within an organization for their own unique applications. This model also allows governance and compliance regulations to remain in place.

2021 was certainly a year of growth for data analytics, with organizations increasingly seeing its value in informing better business decisions. However, much of this deployment has been siloed to individual teams and has prevented organizations from becoming truly data-driven. To get there in 2022, business leaders must focus on increasing Data Literacy, identifying modern and democratized tools, and creating more flexible infrastructures that allow data to be useful to everyone, for various use cases. Data analytics has a bright future in 2022, and it will be exciting to see how it further evolves. 

Leave a Reply

We use technologies such as cookies to understand how you use our site and to provide a better user experience. This includes personalizing content, using analytics and improving site operations. We may share your information about your use of our site with third parties in accordance with our Privacy Policy. You can change your cookie settings as described here at any time, but parts of our site may not function correctly without them. By continuing to use our site, you agree that we can save cookies on your device, unless you have disabled cookies.
I Accept