What do the Google, Salesforce analytics deals mean for CIOs?

Democratizing analytics neutralizes the squeaky wheel

One of the biggest pain points for IT executives has always been the squeaky wheel: How do CIOs  balance demands from the loudest voices with the input of the well-informed voices? For example, a good product manager may constantly get feedback from customers, salespeople and developers on what the product needs. But these perspectives are often skewed by the most vocal customers, prospects, sales staff.

Torsten Volk

"Tools like Tableau, Looker and Periscope provide a "sanity check" by making it possible for people outside of IT to dig into the data," Volk said. They can look at key metrics such as how much pipeline revenue is associated with which group of customers in the CRM; what people are complaining about in the support ticketing system; and what the IT operations log is saying about capabilities that are painful to maintain. The data helps managers decide if they can shift investments in those areas everyone seems to be clamoring for into areas that might in fact have a bigger strategic impact. And with these tools now incorporated into Google's cloud platform and Salesforce, CIOs whose organizations subscribe to these platforms will be able to offer them users.

Different vendor niches, impact on enterprise plans

While the acquisitions were big news for the respective acquirers and the data analytics market, the deals are not likely to have a big ripple effect on CIOs' analytics strategies -- at least for now.

James Kobielus

James Kobielus, SiliconAngle Wikibon lead analyst for data science and AI, pointed out that although all three acquisitions are in the analytics space, the acquiring companies don't necessarily compete on a substantive level.

"Salesforce, Google and Sisense are coming from distinct enterprise solutions niches and are using these acquisitions to flesh out distinct portfolios and strategies," he said.

Thus, the acquisitions likely address different initiatives that IT executives may be spearheading in their enterprises, including:

• 360-degree customer analytics: Salesforce's acquisition of Tableau adds a strong business analytics front-end to the former's customer relationship management services.
• Multi-cloud intelligence: Google's acquisition of Looker extends the former's multi-cloud strategy into business intelligence, data-driven visualization, and rich analytics that pull data from throughout the multi-cloud.
• Democratized AI development: Sisense's acquisition of Periscope Data rounds out the former's strong BI offering with statistical modeling tooling that is suited for the next generation of AI and machine learning developers who don't have a background in data science.

Moreover, Salesforce and Google have taken pains to assure customers that they can keep their existing analytics tools.

Tableau, for example, will be a stand-alone brand or offering under Salesforce and unlikely to change enterprise customers' adoption or usage of competing BI or visualization tools, such as Microsoft Power BI and MicroStrategy, or on the other CRM SaaS offerings out there, Kobielus said. The question around this deal revolves around its impact on Salesforce's product line and revenue picture, he added.

Google's acquisition of Looker may cause some Google Cloud Platform (GCP) customers to adopt Looker for multi-cloud BI or visualization. But Google has said it will not require its platform customers to use, so there's little likelihood that GCP customers who use Tableau, QlikView and other well-established BI tools will see any functional or economic reason to dump those tools, in Kobielius' view.

Sisense's acquisition of Periscope Data involves two vendors that are nowhere near the top of their respective niches, he said. Neither of their solutions is a consolidation target now, and they are unlikely to develop into such targets once the combined vendors start the process of consolidating branding, functionality, pricing and support.

Watch out for lock-in

Still, the acquisitions will eventually require CIOs to make certain choices. The analytic companies snapped up in recent weeks are all about making it as easy as possible for business users to query corporate and external data without the need for a massive BI implementation project. Their focus is on experimentation and end-user enablement to achieve early successes that then fuel the appetite for building out a comprehensive enterprise analytics strategy.

The moment an enterprise moves beyond this experimentation stage and into the building of data-as-a-service platforms, that's when these enterprises have to start worrying about the implication of these acquisitions in terms of lock-in or of the entire platform, Volk said.

This kind of lock-in happened during the heyday of vendors acquiring multi-cloud management platforms and then focusing the premium capabilities of these platforms on their own cloud technologies. "None of these [acquired] platforms did well and most of them have not survived," Volk said.

Data integration down the road

Even if these acquisitions don't lead to lock-in, they could, however, create different challenges around data integration, said Dave Chapman, cloud strategist at Cloudreach, a cloud computing consultancy.

Dave Chapman

There is some risk around what proportion of the future investment from the acquired companies will be targeted at deep integrations with parent company technology, leaving wider integration capabilities underdeveloped. "Right now, the acquirers Salesforce, Google and Sisense are at pains to reassure customers around the independence of their recent acquisitions, but how long will that last?" Chapman asked.

Whether using Google-Looker or Salesforce-Tableau or Sisense-Periscope Data mixes, CIOs have got a lot to be pleased about, as deep integrations are now even more likely, making it easier to streamline more processes. But those who were looking to purchase an analytics or visualization tool must consider their wider estate as part of the purchasing strategy -- and this is now likely a larger consideration than it was last week, pre-acquisitions, Chapman said.

Blend the teams too

"It's important to remember that these tools are still just tools," said Cat Iuga, president of Cognetik, an analytics and data science firm. Enterprises need smart people at the wheel who can drive value out of these tools.

Iuga advocates that as enterprises consolidate their analytics tools, CIOs should also blur the lines between teams by consolidating them. Get the marketer to learn a little data science and the big data engineer to learn data analysis. Make sure your teams are trained on what the data represents and how to use it to their advantage. "Unless you blend team capabilities, they won't fully maximize the value of blending these analytics tools,"Iuga said.

However, Iuga also cautioned that just because an acquisition takes place and sales teams have a new pitch, it doesn't mean their respective tools are now fully integrated. It takes time for that integration to be executed well. "Don't rush into replacing tools or buying complementary ones," Iuga said. Also make sure to perform well-designed proofs of concepts and understand not only how these tools work together, but how to increase revenue by using them together.

Paul Appleby

In the meantime, the acquiring companies will face a challenge around how quickly and smoothly they can integrate the acquired companies. "While they're focused on the integration, there's no doubt the rest of the industry will continue to focus on innovation and new customer acquisition," MicroStrategy's Owen said.

Enterprises are moving beyond data as a passive asset toward treating it as a dynamic asset that drives everything from customer engagement to autonomous vehicles to efficient energy consumption.

"Any corporate doubts that the Fourth Industrial Revolution is all about data have been put to rest by the timing, size and scope of these acquisitions," said Paul Appleby, CEO at Kinetica, in an- database platform. "These acquisitions represent a consolidation of the last wave of data innovation."