Automation is expected to be one of the biggest business intelligence trends of 2022.
But not merely process automation, which is becoming common in data management to reduce certain tasks that need to be done repeatedly. Instead, industry insiders predict 2022 will be the year analytics vendors add more automated insight delivery capabilities to their platforms, enabling users to take action in real time.
In addition to automation, BI users can expect to see further development of natural language processing and AutoML capabilities, scenario planning tools and more money moves in the business analytics market.
1. Automation trend continues
As 2021 wound down, Tibco was attempting to acquire Blue Prism, a robotic process automation (RPA) vendor, before the deal fell through. In addition, Alteryx and Qlik formed partnerships with UiPath, another RPA vendor.
Those moves extend existing automation capabilities, and experts expect vendors to make automation even more of a focus over the next 12 months.
Together, AI and automation will revolutionize the way organizations utilize their analytics platforms. Mike LeoneAnalyst, Enterprise Strategy Group
“Together, AI and automation will revolutionize the way organizations utilize their analytics platforms,” said Mike Leone, an analyst at Enterprise Strategy Group.
“Automation around prescriptive analytics is the [BI trend] that gets me really excited,” said Ashley Kramer, chief product and marketing officer at Sisense. “I think that is the one that really starts to make workers more efficient and really makes people start using data in intelligent ways to become better at their jobs.”
Analytics has always been descriptive, showing what has already happened. Its next stage was to become predictive, demonstrating what is likely to happen next. And now, analytics is becoming prescriptive, recommending what organizations should do next.
“Where we see the world going is, ‘Don’t make me figure out where to go to find that prescriptive analytics outcome,’ and infuse it with whatever workflow it is,” Kramer said. “It’s pushing, it’s showing up in the experience.”
For example, health care workers spend a significant amount of time in their organizations’ health care management system. Salespeople, similarly, spend the bulk of their time in customer relationship management systems.
“Show up right there, without them asking,” Kramer said. “You can program KPIs in any platform, but alert me when there’s trouble in an account, when there’s a hot customer — those kinds of things — without me having to go and ask for it.”
Similarly, Elif Tutuk, vice president of innovation and design at Qlik, expects to see further advances in automation capabilities in 2022. More than just deliver insights, however, she expects analytics platforms to automate actions as well.
Traditionally, Tutuk noted, BI has been able to provide insights to users, but it’s then been up to those users to figure out how to take subsequent action.
“With automation platforms, [vendors are] making the goal of BI a reality, which is compelling actions,” she said. “It’s being able to tie insight generation to trigger automations based on the analytics findings. That can be done fully automated or with a human in a lookout perch, whereas a user might be looking at a dashboard and realize something but can’t trigger action right from the dashboard.”
2. Natural language processing
While automation enables action, so, too, does natural language processing (NLP).
With advancing NLP capabilities, vendors are attempting to make their platforms accessible to more users. Depending on the source, it’s estimated that only one quarter to one-third of employees use data to inform their decisions.
Analytics industry experts predict advances in natural language processing technology and adoption will trend in 2022.
Given that most people don’t have backgrounds in computer science and statistics, there are barriers to working with data. Most employees don’t know how to code, and they don’t have the requisite training to interpret data and ask the follow-up questions that lead to insights.
Augmented analytics tools aim to reduce those barriers by guiding business users with no-code capabilities, including NLP features that enable data queries in natural language with written or spoken words. Adoption, however, remains low, according to analysts who note that the actual capabilities of NLP tools are slowly catching up to their promise.
However, adoption of AI capabilities is expected to pick up in the year ahead.
“Many organizations are behind the curve in their use of capabilities like augmented analytics, natural language querying and natural language processing,” Leone said. “Organizations will increasingly lean on AI to help improve data quality and data discovery as they look to ensure more trust in data and the insight derived from analyzing it.”
David Menninger, an analyst at Ventana Research, similarly expects to see more NLP adoption. But because NLP tools still struggle with some of the nuances of language — synonyms, words that sound similar, words that have one meaning for one organization and a different meaning for another — and because they can be onerous to implement, he doesn’t expect to see it explode in 2022.
“I think NLP will continue to grow in usage,” Menninger said. “I think it will continue to improve and will help, but I don’t think it will be the breakout year, so to speak. I think there’s more work to be done, both on the technology and on organizations’ willingness to utilize the technology.”
Just as NLP tools are designed to enable self-service query and analysis, AutoML tools enable self-service data science. Using no-code/low-code tools, business users can build, train and deploy data models for deep analysis and insight generation.
For example, Tableau has made the concept of business science a priority. First introduced in March, business science is essentially self-service data science enabled by augmented intelligence and machine learning.
Meanwhile, Qlik acquired Big Squid specifically for its AutoML capabilities and Alteryx made AutoML a centerpiece of its May 2021 platform update.
And industry insiders say more is coming in 2022.
“Predictive analytics will become more accessible,” said Nelson Petracek, Tibco’s chief technology officer. “The technology will be made available to broader audiences, not just data scientists, through the use of continuously improving tools and model-driven approaches to development.”
Likewise, Menninger expects vendors to continue to add and improve AutoML capabilities over the next 12 months.
“I think we’ll see significant strides in AutoML,” he said. “We’re getting to the point where the output of AutoML is useful. It’s not going to be as robust as a trained data scientist, but it certainly has gotten to a point where it’s useful, so I think we’re going to see more use of AutoML by people that are not necessarily trained data scientists.”
New AutoML capabilities don’t come without consternation, however, Menninger added.
Just as self-service BI requires a stringent data governance framework to protect organizations from exposing sensitive data while enabling end users to confidently work with data, self-service data science need to include protective measures.
“More AutoML use will bring with it some challenges — governance issues and people possibly over-relying on something they don’t understand,” Menninger said. “Before you put something into production that is a daily business process, it has to require a team of data scientists to review it and oversee it and make sure it’s governed.”
4. New areas of emphasis
While many BI vendors already have automation, NLP and AutoML capabilities, there are features few analytics vendors offer that analysts expect to become more ubiquitous in 2022.
Among them are tools to support environmental, social and governance (ESG) initiatives and scenario planning.
For reasons including regulatory compliance and altruism, many organizations are undertaking ESG projects. For example, oil and gas and other carbon-intensive industries have instituted measures to increase sustainability, and organizations need to reduce their carbon footprints and measure their progress.
One of the business intelligence trends to expect in 2022 is more tools to enable ESG reporting while application vendors and system integrators develop more ESG software and services, according to Doug Henschen, an analyst at Constellation Research.
“What businesses need is more consistency and practicality across the patchwork of standards and regulations across the globe,” he said. “Tech can help organizations be transparent and meet targets, but it’s harder when there are competing and fuzzy goal lines.”
“The ‘E’ in ESG has been leading the way, with oil and gas and other carbon-intensive industries long ago embracing reporting standards and ways to measure progress toward sustainability goals,” Henschen said. “But environmental, social and governance expectations are rising across all industries, with asset managers, investors, activist groups and forward-looking companies leading the way.”
Menninger, meanwhile, said he expects to see more vendors add planning capabilities.
Historically, planning tools that examine different business scenarios have been offered by a separate set of vendors from those that offer BI and analytics platforms. Envisio, Adaptive Planning and Cube all focus on scenario planning.
Now, however, some analytics vendors are adding scenario planning tools, and that will accelerate in 2022, according to Menninger.
“I’m seeing a trend bubbling up around planning — what-if analysis,” he said. “I’m seeing more vendors investing in and bringing planning and what-if capabilities to market in combination with other types of analytics. It may not be a breakout year, but perhaps a year in which the level of interest rises significantly.”
“When I’m seeing the major platform vendors, the leaders in the visualization space, adding more planning capabilities — that tells me that’s about to jump,” Menninger said.
5. Money moves
Beginning with Qlik’s acquisition of Podium Data in July 2018 and ending with Salesforce’s acquisition of Tableau in June 2019, consolidation has been a significant BI trendin recent years.
During that 12-month period, Sisense purchased Periscope Data, Alteryx bought ClearStory Data, Logi Analytics acquired Zoomdata and Google purchased Looker.
Then consolidation slowed, and other than Tibco’s October 2020 acquisition of IBI (formerly Information Builders), acquisitions have been about large, established vendors acquiring startups.
In the meantime, there’s been an influx of capital into analytics vendors.
ThoughtSpot has raised $348 million in two funding rounds since the start of 2019 and is now valued at $4.2 billion; Databricks raised $1.6 billion in funding in August 2021; Snowflake set a record for tech companies in September 2020 by raising $3.4 billion through its initial public stock offering; and Informatica returned to the public markets in October 2021 by raising $841 million after being taken private in 2015.
Meanwhile, the stock prices of MicroStrategy and Domo hit all-time highs in 2021.
Some of that cash could be used to fuel significant acquisitions, said Donald Farmer, founder and principal of TreeHive Strategy.
“In terms of big stories, where is some of this money going — when is Snowflake going to buy someone, and what is ThoughtSpot going to do with their funding? They’re not just giving their developers a raise, so they’re going to do something with it,” Farmer said. “They’ve hinted that there are acquisitions to come.”
Even smaller vendors, such as Mixpanel and Sigma Computing, have raised substantial capital, with Mixpanel securing $200 million on Nov. 18 and Sigma securing $300 million on Dec. 16.
“We’re seeing huge amounts of money raised, so where’s that going to go? What is Mixpanel going to do with $200 million?,” Farmer said. “There’s a lot of money being poured into data and analytics companies, and it will be interesting to see where some of that gets spent.”
Enterprise Strategy Group is a division of TechTarget.
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