Collaboration looks like the next big analytics trend.
The sudden increase in remote work resulting from the COVID-19 pandemic led to a sharp increase in the use of collaboration tools such as Slack, Microsoft Teams and Google Docs.
Numerous analytics vendors responded by developing integrations with the collaboration tools, enabling users to embed analytics assets like dashboards and reports into the collaboration tools so they can work in a single environment.
Some, however, went further and built collaboration capabilities into their own platforms to enable employees working from separate locations to work together on analytics in a virtual hub.
Observers expect to see more collaboration enabled by data and analytics vendors, and expect that to be one of the major analytics trends during the second half of 2021.
"I don't see enough collaboration yet, but I absolutely see a trend toward it," said David Menninger, senior vice president and research director at Ventana Research.
Similarly, Mike Leone, senior analyst at Enterprise Strategy Group (ESG) said he expects to see more collaboration capabilities included in analytics platforms and added that they're necessary.
"There are components of collaboration that really need to be emphasized," he said.
Collaboration, however, isn't the only analytics trend industry experts expect to see during the final months of 2021 and into 2022.
In addition to established trends such as embedded analytics and real-time BI, analysts expect less distinction between different operations departments as the lines between developers, data scientists, data analysts, system administrators and other IT professionals continue to blur, and more inclusion of data and analytics tools into a single environment.
And as always, they expect vendors to add more augmented intelligence.
When the pandemic struck and offices were shuttered, meetings that had been held in conference rooms were instead done over Zoom, conversations with co-workers that took place in offices or over coffee in a cafeteria instead took place on Slack and Teams, and work on team projects had to be accessed online with such tools as Google Docs.
Analytics was no exception.
"The whole purpose of working with data is to make some sort of informed decision, and I rarely make those decisions myself unless I'm a sole proprietor," Menninger said. "I'm working with colleagues or I'm working for a manager and preparing an analysis, and it has implications across the organization. Typically, that's a collaborative process."
In response, data and analytics vendors are starting to make collaboration a priority.
Tableau, for example, included a capability called Collections in its most recent platform update, enabling users to easily curate content so it can be shared with colleagues for collaborative purposes.
Likewise, in December 2020, ThoughtSpot introduced ThoughtSpot One, a search-based tool inspired by social media platforms such as TikTok and Instagram that enables customers to use natural language processing to find analytics content created by others in their organizations, then modify the content and share it with others.
Microsoft, meanwhile, unveiled Goals in Power BI in preview May 2021. The tool, when released, will enable customers to curate metrics and business objectives to monitor the progress of analytics projects, share updates and take proactive action when goals aren't being met.
With such tools, users across different departments and in different locations are able to work together to ultimately enable data-driven decision-making.
"One of the things we're seeing from a BI standpoint is the involvement of different personas across the business," Leone said. "It's the need to involve senior leadership, IT, data science, business data analysts, developers, line-of-business leaders. It's involving pretty much everybody across the organization, from C-suite level all the way down to an end user."
But analytics vendors aren't yet enabling users to benefit enough from that top-to-bottom involvement, according to Menninger. Tools such as the ones developed by Tableau, ThoughtSpot and Microsoft are not yet the norm.
"I don't think we're quite there yet," Menninger said. "I see some vendors with some pretty strong collaborative capabilities in their analytics and data processes, but not enough."
Lines have been drawn across organizations.
There are DevOps, DataOps and MLOps teams. There's data governance and there's analytics governance.
Meanwhile, organizations have one tool for data capture, another for cleansing and preparation, and still another for visualization. And within BI and analytics platforms, there are a host of different tools for data modeling, data visualization and data storytelling, but they're done in separate parts of the platform.
Wayne EckersonFounder and principal consultant, Eckerson Group
All those lines, however, are softening. And an analytics trend that could gain momentum in the second half of 2021 is more unification.
Yellowfin, for example, recently updated its platform to create a more unified experience by enabling users to embed data storytelling capabilities on dashboards. Similarly, Domo's latest update consolidated a series of capabilities for embedded application development under a single umbrella to streamline the development process.
"Convergence continues in [analytics]," said Wayne Eckerson, founder and principal consultant of Eckerson Group. "Data tools are converging into a data platform, BI tools are converging into an analytics platform, and those two platforms are converging into a unified data and analytics platform."
Similarly, Menninger said he's seeing some convergence beginning to take place, but not enough yet.
In particular, domains such as DevOps and DataOps, and different governance guidelines for data and analytics, are limiting.
"I hope for less of a distinction between data and analytics," Menninger said. "The way we see [distinctions] manifesting themselves is in all these separate catalogs. As a user or line-of-business person wanting to work with data, I want a catalog that crosses all those things, a governance process across all of those things, operations across all of those things."
He added that he expects to see some of the division ease, but that it will take time.
"I think we'll start to see more of those walls break down, but not enough," Menninger said. "I think we'll see some progress on that front, and I certainly hope to see more of it."
AI still rising
Augmented intelligence has already been a significant analytics trend in 2021.
The pandemic forced an increased reliance on self-service capabilities, and by reducing the need to know code -- enabling such capabilities as query and analysis using natural language processing and model development with automated machine learning (AutoML) -- AI is the enabler of self-service analytics.
As a result, AI and machine learning capabilities have been at the core of a host of recent platform updates.
The latest version of Tableau's platform includes updates to Ask Data and Explain Data, tools that enable users to query data and get insights with NLP. Qlik's focus is now on the concept of active intelligence, which relies on AI to automate tasks and send push alerts that deliver insights in real time. A recent Oracle update also centered on new ML and NLP capabilities.
Much more, however, is to come, according to Leone.
"This is the year of augmented analytics," he said. "We've heard it for some time, but that is the top capability that organizations plan to invest in over the next year in support of BI and analytics."
According to ESG research, the use of augmented analytics will increase 88% over the next 12 months, spanning the second half of 2021 and the first half of 2022, Leone continued.
"It's tied to self-service, but it's about AI helping you get there faster," he said. "As organizations look to either maintain their competitive lead in the market or catch up to the competition, I think augmented analytics is going to go a long way. There are chatbots, query recommendations, all these different components. That's one area that's going to be so hot this year."
Similarly, Menninger said he doesn't expect investment in AI and ML capabilities to slow down anytime soon.
One important use case, he noted, is applying AI and ML to help users discover exactly what is important in their data. Another, he added, is using AI and ML to discover correlations.
"The AI trend continues -- AI and machine learning," he said.
A look into the near future
Beyond the incorporation of new tech tools, significant financial developments in analytics and data management are expected over the final six months of 2021.
Two years ago, just before the midpoint of 2019, Google acquired Looker for $2.6 billion, and then just days later, Salesforce bought Tableau for $15.7 billion.
A year later, Snowflake filed for its initial public offering, hoping to raise between $75 and $85 per share. Instead, in September 2020, Snowflake went public at $120 per share and shattered the previous record for tech companies by raising $3.4 billion in its IPO.
Databricks could be the next major tech IPO. And among analytics vendors, ThoughtSpot has long been rumored to be positioning itself for an IPO. If it does go public, and if the IPO generates significant interest, it will be a good sign for not only ThoughtSpot but BI and analytics as a whole, according to Menninger.
"IPOs are certainly interesting to watch," he said. "They give a broader assessment of how the market values these technologies, both the individual technologies and the technology category."
A strong showing by ThoughtSpot, he continued, would be a strong endorsement of NLP, which Menninger said is an important technology because it enables business users to interact with data without having a strong background in data literacy.
"If they get a high valuation, that might prompt more investment in this area and more investment in those capabilities, which I think are really important to making analytics finally reach the masses," Menninger said.
Leone, meanwhile, said that the second half of 2021 might be when Snowflake finally makes a substantial acquisition.
The data cloud vendor has established a slew of partnerships to increase and improve capabilities, but it still lacks significant BI capabilities of its own.
"Snowflake is a really good example of a company that I would be shocked if they didn't make an acquisition soon," Leone said. "They have a presence in data science and AI via a ton of partnerships, but they're going up against some of the big cloud providers who enable businesses to really transform with the cloud and do more."
In addition to Google acquiring Looker in 2019, Microsoft has developed Power BI into a strong analytics platform and even AWS now offers Quicksight.
"Maybe Snowflake needs to make an acquisition to have a better foot on the ground when it comes to that next level of innovation, that next level of data insight, leveraging AI and having it be their own," Leone said.
Beyond individual vendors making moves, Eckerson said he expects to see more data exchanged between organizations, both for public good as well as for profit.
Snowflake and AWS, in particular, have made data sharing simple, he continued. And just recently, Databricks took steps to enable data sharing.
"Something that's exploded is the whole data exchange -- data sharing and data monetization," Eckerson said. "There are a lot of companies that have recognized the need for external data to support data science projects and machine learning. These next 12-18 months will the year of external data and sharing that data with other companies."
Enterprise Strategy Group is a division of TechTarget.