Data Analytics Trend : 5 Key Data Analytics Trends For 2021
By: Express Analytics
Tags: Data, Big Data, Data Analytics

2020 was a year when the COVID-19 pandemic shook up the world of business and commerce, adversely affecting almost every sector save data analytics. In the new year, the pandemic will continue to remain on everybody’s minds, despite vaccines in the market. The virus’ lingering after-effects will continue to impact businesses.

2020 will also go down in history as the year when businesses and customers were forced to go digital. From hereon, we at Express Analytics foresee that every enterprise will have to be proactive (not reactive as we saw prior to 2020) where data and analytics are concerned. That’s the new normal.

Businesses must look at the coronavirus pandemic as an opportunity; a chance to implement, if not done already, digital technology to tackle the market chaos.

Keeping this in mind, here are 5 trends we forecast for 2021 with tips on how to use them to your business’ advantage:

1. Yes, Data and Analytics Are Moving To The Cloud

Initially, enterprises were reluctant to move their data storage to the cloud. One reason for this was that the cloud was built for transactional purposes, not for the memory-hogging analytics.

That is no longer the case. With cloud technology getting swifter, smarter and flexible, this year saw many organizations moving their data warehouses into the cloud or go the hybrid way, i.e. use a combination of cloud and on-premise warehouse.

Earlier, data warehouses were to be found in physical storage servers like Oracle Exadata. Now, some of them at least have moved on to the cloud, availing of services by providers like Amazon, Microsoft, and Google.

Aiding this journey is the advent of commercial homomorphic encryption. This permits the performance of computational tasks on data without ever having to decrypt it. Which means — without compromising data security. Which also means the holder of the decryption key does not necessarily have to be in the same room, figuratively speaking, as the person doing the analysis.

Data security is one of the last hurdles in the way of cloud computing. Many organizations were not adopting the cloud because of security issues since processes like mining and the analysis of data in the cloud cannot happen if the data is encrypted. Homomorphic encryption helps solve this fundamental problem now.

Here’s what Gartner has to say about the cloud: It’s a given. Public cloud services will be essential for 90% of data and analytics innovation by 2022. Cloud-based AI will increase 5x between 2019 and 2023.

What’s in it for your business: Today’s cloud-based data warehouses offer you the option of deciding what data goes to the cloud and what stays on-premise. Most offer end-to-end data warehousing which allows your business to enjoy the benefits of data analytics right out of the box. All of it also means making your enterprise more agile.

2. Data And Analytics Will Be Even More Democratized

Even before COVID-19, the lines between the IT department and the rest of the enterprises had started to blur where data utilization was concerned. The pandemic riddled 2020 has softened that line even more.

Data is no longer the sole purview of the IT team nor is analytics limited to the CSuite. In 2021, more efforts will be put into seamlessly integrating data platforms, including easy-to-understand visualization boards within an enterprise. The business of self-service analytics tools, too, will continue to grow.

We are in the age of the truly data-empowered. Data has become more democratic as enterprises have started allowing employees at various levels to explore and analyze data literally from their desktops or on their hand-held devices. Today, with the advancement in technology and computing, enterprises are deploying self service business intelligence (BI) models. These empower the line employee to find patterns in his data, find context, and collaborate with other team members to effectively realize the maximum value provided by the insights.

The modern-day version of BI platforms is driven by artificial intelligence (AI) and are almost fully automated. What’s more, such self service tools help increase collaborative efforts between all departments — from IT to Sales.

What’s in it for your business: Traditional BI delivery models do not offer the level of agility that today’s global business environment demands. With data channels and data volumes multiplying in real time today, your business could do well by introducing self service tools to leverage the full value of this data. Such tools are also cord-cutters, being less reliant on IT.

3. 2021 Will See Faster, More Automated AI & ML, And More Of NLP

In 2021, both, data classification as well as data modeling will get even more automated. Which, in turn, will result in even more accurate and actionable insights. When businesses are able to pick up market trends early, it will help them stay ahead of the competition.

NLP has made analysis more user friendly by translating natural language queries into the language needed to obtain results. It can help extract vast amounts of unstructured data that have been made available by the ever-increasing use of social media use, online reviews, etc.

NLP now allows a computer to understand the language of humans, thus making sense of customer conversations, and categorizing them. Which means, the use of NLP in online social conversations can help recognize a sentiment on a particular subject, probably in real-time, thus giving the brand an opportunity to change course on a product, midway through its marketing campaign.

Gartner has forecast that 75% of enterprises will shift from piloting to operationalizing AI by the end of 2024, driving a 5x increase in streaming data and analytics infrastructures. There are challenges with current approaches. Pre-COVID models based on large amounts of historical data may no longer be valid.

What’s in it for your business: The increase in the sophistication of the NLP will see a proliferation in user interfaces using natural language and NLP-based analytics applications in 2021. As AI technology matures, the computer will get better at “understanding” human language queries, learn about the various semantic relations and inferences in a query, and start delivering even real-time business intelligence to users. All this means your business can use AI, ML and NLP to turn complex data into actionable business intelligence. NLP, especially, will lead to the transformation of analytics results into stories, thus speeding up the implementation of analytics in every sphere of life, and in every unit of your enterprise, helping you achieve your business goals even faster.

4. Customer Personalization Will Put Consumers Firmly In Driver’s Seat

The way 2020 played out, it put consumers firmly in control, be it in retail or in healthcare. More customers/users came online than ever before because of work-from-home routines, forcing businesses to digitize. Digitization meant more data and a better view of your customer.

Data science is now rewriting the dynamics of business. In the coming year, we will see more businesses focus on delivering a highly personalized experience to their customers — the right offer at the right time in a customer’s buying journey.

What’s in it for your business: With increased digitization, it is clear that customer personalization must become part of a company’s business strategy in 2021. You need to meet your customers where they are. To succeed at customer personalization, your brand needs to design a data-driven “Personalized Customer Experience Plan”. After all, an “engaged” customer will eventually be a happy customer.

5. Customer Data Platform Landscape Will Continue To Grow

Because of the increased digitization that 2020 saw customer data platforms (CDP) were much in demand. A CDP is a sophisticated data hub where all things related to data converge — from data sources to customer information. Every customer inevitably leaves behind information while interacting with a brand. When they surf the Internet or interact with companies using other online and offline channels like websites, e-commerce platforms and in-store interactions, their footprints can be tracked.

We foresee the popularity of the CDP continue to grow in 2021, too, and even beyond. In fact, contrary to popular thought that a CDP is only for B2C businesses, we saw many more B2B companies, too, deploying the same this year. There’s no going back from transacting online, which means more data flowing into your enterprise.

A customer data platform provides a 360-degree view of your customers’ journey and captures their interactions with your brand. It also updates your data base as new data comes in from various channels. A CDP then gives structure to this data and matches it to customer profiles to help businesses better engage with their customers.

What’s in it for your business: To help build loyal relationships with your customers in order to offer them the product or service they are looking out for, your business will have to invest in a customer data platform. A CDP can help you visualize instant insights from your data in real time. You may drill down as much as you want to capture the “connect” between what looks like unrelated data.

It also helps you with customer identity resolution and customer segmentation, which, in turn, will help your business develop focused strategies to hold on to its top-paying customers. Or, to re-engage those clients who haven’t purchased in a while.

In conclusion: COVID-19 has accelerated digitization, setting a new norm of doing business. Data is now, more than ever, a key ally of industry. The new year will see sustained efforts in bridging the gap between data analytics and industry needs. Actionable insights will be the focus. For that, businesses will be investing in AI/ML run platforms and visualization techniques that make analysis easy to understand throughout the enterprise.