Looker & Tableau Acquired: The State of the Analytics Market

Two recent acquisitions are making headlines in the tech space as enterprise software companies vie for a piece of the business analytics pie.

First, Google announced that it would be acquiring Looker on June 5, reportedly to leverage the platform’s data visualization capabilities for Google Cloud services.

Days later, Salesforce announced its upcoming acquisition of Tableau, a deal scheduled to close on October 1st of this year.

It’s not yet clear how these analytics platforms will be made accessible to business users or how they’ll be entrenched in Google and Salesforce’s mainstay software.

Yet, in light of this news, the analytics space is buzzing with questions about the state of the market and the role of analytics in the larger scheme of business intelligence.

What the Looker and Tableau Acquisitions Signal About the Future of Analytics

These back-to-back purchases demonstrate that tech companies are investing in analytics as a critical aspect of their enterprise suites.

Users, perhaps now more than ever, need tools that can interpret the astronomical amounts of data that most companies wield— a demand that Salesforce and Google, in their data-centricity, would be well aware of.

For the average business user, analytics are a means of transforming abstract data into something more actionable. The data visualization capabilities of platforms like Looker and Tableau are one method of providing more insight into metric relationships by indicating general trends, outliers, and so on with customizable graphs and charts.

But, the hunger for analytics solutions seems to point to a larger need for the kind of tangible insights that lead to data-driven decisions.

Beyond visualizations, advanced technology like natural language insights can weave complete data narratives that address the causes beneath the numbers on the surface. Data exists as a complex web of relationships, and trends that can be captured in visualizations are part of a larger story.

The more companies invest in tech that drives insights, the more innovative, intuitive, and routine insights will become in the decision-making process.

As the need for user-driven, insight-fueled analytics in business intelligence software grows, so too has interest from outside software companies, like Google and Salesforce. Likewise, this interest will help propel the analytics market forward, as independent platforms continue to refine their offerings to differentiate themselves with better, faster, and more advanced insights capabilities.

The market is ripe for innovation— which brings us to the next frontier in the space.

AI: The Next Frontier of the Analytics Market

Analytics solutions help users make smarter decisions based on data. In a sense, they enhance our insight and intelligence.

It’s a logical, natural step that the future of analytics will be led by AI. 

AI continues to bridge the gap between a user and the data they seek to interpret. AI is adept at the tasks that are time-consuming, laborious, and often frustrating for employees.

For example, AnswerRocket’s AI-driven analytics software leverages machine learning and natural language technology to generate the data narratives discussed prior. In practice, this means AnswerRocket parses through an entire data warehouse to identify the most important and relevant data relationships, triggered by user queries like “how did Brand A perform last quarter?” or “why are sales down?”

Machine learning algorithms perform this analysis in minutes, a feat that would take a person hours or days, depending on the complexity of the query and the amount of wrangling they’d have to do to gather, prep, and analyze all of their relevant data sources.

AnswerRocket makes quick work of evaluating all potential combinations of data, testing every possibility without bias.

Once the analysis is complete, AnswerRocket generates data visualizations and natural language narratives that explain and reveal hidden insights from the data, such as key drivers, trends, correlations, and anomalies. Where possible, the opportunities with the most ROI are also presented, guiding the decision-making process for business users.

This level of AI is innovative and unmatched in the analytics market.

Learn more about AI analytics with this ultimate guide.

How the Google and Salesforce Acquisitions Can Expand the Breadth of Analytics Use Cases

These acquisitions provide an interesting opportunity to see how analytics can be adapted and refined for the wide variety of use cases that customers of Google Cloud and Salesforce no doubt have.

At AnswerRocket, AI has been the means of tailoring analytics to different roles, departments, and industries.

Specifically, AnswerRocket employs specialized machine learning algorithms purposefully designed to address specific business use cases. CPGs can, for example, easily automate time-intensive market share and brand health analysis with algorithms that break down these metrics in-depth. Algorithms designed to run financial analysis quickly reveal core contributors to top-line growth and bottom-line profits.

AI can automate tasks like market share analysis.

We’re continually developing new algorithms for automated analysis to meet the growing and diversified needs of companies who’ve invested in our AI-driven analytics.

The analytics buy-in from Google and Salesforce can similarly lead to more nuanced applications of analytics as a whole. In a future state, companies could come to expect tailored analytics that speak to their unique needs.

Ready to get ahead of the analytics curve? Try AnswerRocket today!

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