Top 3 Data and Analytics Trends to Watch in 2022

Data initiatives are delivering value for more companies, giving rise to these data and analytics trends.

By Michael Brenner

By Michael Brenner September 21, 2022

The ubiquity of data, analytics and a knowledge-driven work ethic has been the hallmark of business since the turn of this millennium. It coincided with the rise of the internet. Increasingly, businesses and organizations are finding great value in the data they generate and collect. So much so that many use the phrase: data is the new oil. Data and applications are becoming the lifeblood of business, and rapid innovation in IT technologies is helping enterprises evolve and thrive in the digital age.

A growing majority of today’s business leaders believe in the power of data-driven insights to steer decision-making and drive profits. Most have or are implementing data-focused organizational changes, with 92.1% reporting that their data initiatives deliver a return on investment. Nearly three quarters – 73% – of large organizations have appointed chief data or analytics officers, marking a striking increase from 12% in 2012.

However, even as data and analytics are more infused with decision-making across all levels of an organization, few businesses seem to accurately understand the stakes involved, as 90% of IT officers believe leaders in the boardroom compromise data security and best practices for the pursuit of other goals.

Advantages of Data-Driven Decision Making.

Image Source: Statistics

Looking at the big picture, it’s clear that data and analytics have transformed the way business is done. A recent McKinsey study titled The Data-Driven Enterprise of 2025 contends that within three years, “smart workflows and seamless interactions among humans and machines will likely be as standard as the corporate balance sheet, and most employees will use data to optimize nearly every aspect of their work.”

Image Source: McKinsey

Data makes the world go round. Powerful advances in data collection technologies and business intelligence platforms help companies keep better track of market variables. Insights from this kind of data help leaders make informed decisions and grow their businesses. There are three critical trends in data and analytics that no business can afford to ignore:

1. AI and Automation Become All-Pervasive

It seems like yesterday when marketing automation burst into the market and simplified large swathes of branding and promotion activities. Similarly, most analytics tasks are now automated, leaving data scientists free to interpret and apply their learnings to offer more value to their organizations.

Recent Gartner studies show that by 2025, AI-based data models will replace 60% of existing traditional models. Additionally, infrastructure design will reflect these changes as well, as 50% of enterprises –up from 10% in 2021 – will develop capabilities for infrastructure automation in hybrid and multi-cloud environments.


IT Automation for the Masses

Increasingly, organizations will offload to AIs and automation a host of data tasks such as data cleansing, generating weekly reports, multivariate testing, and applying predictive analytics. All of this with little to no human input. Naturally, this saved time can translate into better productivity across teams. It can also bring a faster understanding of data that can be applied more quickly to achieve business results.

2. Machine Learning, Artificial Intelligence and Natural Language Querying Skills

There was a time when good data scientists could get by with knowing just how to use a spreadsheet program and know their numbers. Today, data analysts are part developers and part data detectives. They’re expected to know multiple types of databases, use SQL and natural language processing to write queries to pull required data sets, create smart algorithms that “learn” from each cycle and more.

Within the next 10 years, machine learning (ML) and natural language processing NLP) technologies will become mainstream across industries and transform organizational structures and operations.


What Is Predictive Algorithmic Forecasting and How is it Used?

As data sets get larger, more complex, and the time needed to spit out an accurate result keeps getting shorter, artificial intelligence (AI) has stepped in to fill the gaps. Self-learning algorithms offer recommendations based on a combination of static and dynamic variables – something that would have been impossible to pull off manually by a team of data scientists working around the clock.

This combination of machine learning and AI techniques is believed to usher in the era of “Augmented Analytics” Augmented analytics uses algorithms to automate data preparation and insight generation, reducing a company’s dependence on data analysts and scientists in the process.

3. Data Security Takes on a Whole New Level of Urgency

Lately, data breaches have become as common as the stripes on a zebra. From poor user authentication practices to hijacked APIs and user accounts, the various ways data continues to be compromised are mind-boggling. Couple that with the knowledge that identity theft is a real, everyday occurrence that happens to one in three data breach victims.

The cybercrime industry had a global value of $6 trillion in 2021, effectively making it the world’s third-largest economy after the U.S. and China. As the global incident rate for data breaches spiked 68% in 2021 – reaching record levels – managing personal data and securing it from external threats will remain a top organizational priority for the foreseeable future.


4 Database Automation Innovations to Turbocharge DevOps

Encrypting data as it sits in the cloud or physical servers helps prevent potential misuse of the data if it were to fall into the wrong hands. Hashed and salted passwords are already commonly used to protect user data from identity thieves. A Nutanix study titled Top 10 Cloud Security Trends for 2019 delves deep into the 10 most important ways to secure an organization’s data from vulnerabilities at every stage in the usage cycle.

With all the effort that goes into capturing, storing, analyzing and interpreting data, companies look for best-in-class analytics because they understand that business analytics is a critical enterprise asset.

That’s more than can be said for most business processes. As the world rapidly moves towards a data-first approach, it helps to know that smart bets on data and analytics can keep businesses ahead of the curve, the competition, and the threat of obsolescence.

Michael Brenner is a keynote speaker, author and CEO of Marketing Insider Group. Michael has written hundreds of articles on sites such as Forbes, Entrepreneur Magazine, and The Guardian, and he speaks at dozens of leadership conferences each year covering topics such as marketing, leadership, technology, and business strategy. Follow him @BrennerMichael.

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