Why did Google buy Looker for $2.9B and why did Salesforce buy Tableau for $15.7B?
Both of these tools are arguably considered to be among the top Business Intelligence tools that work well in a modern Cloud Data Architecture and support modern Data Analytics, Machine Learning, and Artificial Intelligence. The key to all this is that they support modern Analytics and are at the heart of a high growth opportunity.
A few years ago, Looker and Tableau could only dream about these valuations. Back then, the Cloud-data landscape was extremely fragmented, and solutions were cobbled together in a rush to play in the Cloud ecosystem. Companies were still concerned about the basics such as security, on-prem to Cloud connectivity, how the Cloud fit into their overall technology strategy, how to provision servers and set up an environment, and who they had that even know how everything worked together.
Now the Cloud Data & Analytics landscape is much, much different. Investments in the global analytics space are projected to go from $3B a few years ago to over $90B in 2025, a 50% CAGR.
These trends are indicators that we are in a midst of a technological equivalent of a “perfect storm” – a convergence of at least three major macro-trends that have enabled companies to move beyond the basics and start realizing value from their data assets!
Macro-trend #1 – Cloud adoption.
Amazon, Microsoft, and Google have invested tens of billions of dollars to get companies to the Cloud. One of the first pieces, of course, was security, data privacy, and high availability – especially in highly regulated sectors such as Pharmaceutical, Life Sciences and Financial Services. Next was the ease of environment provisioning and administration. All this investment is paying off. Companies are now more comfortable having assets, even critical data assets, in the Cloud. The TCO and reliability are now in most cases better than on-prem. And more importantly, time to market, flexibility, and scalability are often significantly better than what could be achieved on-prem. By one account, nearly 50% of IT infrastructure spend is now in the Cloud and is increasing. We are even seeing companies with corporate directives to go all-in with the Cloud in the next three to four years.
Macro-trend #2 – New Data Management Capabilities for Analytics.
Data by itself has little value. Value is derived from data assets through Business Intelligence, Data Sharing, and Advanced Analytics. These “value-delivery” methods are supported by a new class of data management capabilities. This evolved class of tools includes Cloud storage, warehousing, data movement, data transformation, and data process orchestration that leverage the Cloud. For Data Management Solutions for Analytics that support BI and Analytics, heavy traditional data management solutions such as Master Data Management (MDM), Data Quality (DQ) projects, structured storage and the like are less critical. Yes, these concepts are important down the road, but to quickly deliver value from your data assets, they need to be right-sized with “good enough” techniques to get you “close enough”. After all, business intelligence, artificial intelligence (AI), machine learning, and advanced analytics are about providing “enough” information, in aggregate, to make decisions that will move the needle.
With all the billions invested by the top three Cloud providers, billions more have been invested in support of analytics and value delivery. Where once vendors could just “lift-and-shift” their solutions to work in the Cloud, now countless more vendors are building born-in-the-Cloud solutions that leverage the separation of compute and storage and other Cloud paradigms. To us mere mortals, this means hundreds of new companies have created unique solutions that provide exciting new capabilities in data management that accelerate modern business intelligence and advanced analytics, taking data projects from bloated and meandering to surgical, fail fast, fail cheap experiments where nearly any sized company can find value in their data assets.
Macro-trend #3 – Advances in Analytics, Machine Learning (ML) and Artificial Intelligence (AI).
When people think of AI, they think of plots of Sci-Fi movies where machines become self-aware and take over the world. This type of general AI where a machine is pointed at all your data and it figures out what you should look at is still years away…thankfully. With today’s AI that most organizations need, humans need to help machines by putting up guard rails. These guard rails are in the form of the business-related question that is being answered. What is the likelihood that a customer will leave? Should I spend time and resources chasing this prospect? What is my competitor likely to bid on that job? Once the question is known, then AI and ML can be used to find more patterns than humans would be able to find. It’s still up the humans to figure out what it means and more importantly what actions to take to improve the outcome, but at least we have actionable data that can move the needle!
In the old days (a few years ago), a data scientist spent a lot of time planning which analytic model and platform to use and to prepare the data in a format the model could accept. These models were created in closed ecosystems, making it difficult to leverage the work of others and fine-tune the parameters. Since modeling was usually done in a “back room”, the output had to be painstakingly integrated with other systems and processes, making time to realize value very, very long. And if the wrong path was chosen, it was a costly and lengthy mistake. Therefore, predictive modeling and advanced analytics were reserved for all but the largest companies.
Fortunately, advanced analytics, ML and AI in the Cloud have reduced the cost and time to develop, test and deploy advanced analytics. This new breed of tools allows companies to quickly try numerous modeling techniques to find the optimal model and shortens the time to market and risk of guessing incorrectly. Better yet, solutions to common business-problems are now able to be shared or API-based analytics services can be leveraged. Most of these tools are now seamlessly being integrated into the Cloud ecosystem to be able to deliver the results at the point of decision, embedded into a workflow or other decision point.
So where is this all going?
The Cloud Data & Analytics space has finally matured to the point where companies are no longer on the “bleeding edge”, but smart companies are still able to be on the leading edge and are being rewarded handsomely with improved corporate performance/profit, increased revenue, more valuable customers, and a competitive, if not sustainable, advantage. So much so, that the projected impact of all this investment on global GDP is expected to reach $16T by 2030.
A critical component to realizing this value that every, yes every, company will need will be a Business Intelligence tool. Since Google and Salesforce want to be a big player in this space, they put a lot of money into the game.
A key takeaway seen here, and one that we are also seeing in the field, is that organizations that are leveraging Cloud Data & Analytics are carving out competitive advantages right now, some of which have the potential to become sustained competitive advantages.
Organizations that are already on a good path can now leverage their successes to accelerate results from their investment – thus increasing their competitive edge and adding substantial value to the top- and bottom-lines. For others, this might be a good opportunity to engage your peers to accelerate your own plans in order to prove that your data is very valuable.
For those still sitting on the sidelines, it is imperative to understand that no industry will be immune to these trends, and this may be just the warning that’s necessary to avoid being disrupted or slowly and painfully becoming irrelevant.
Are you realizing value from your data assets?
Although this space may be overwhelming, there are many seasoned guides (just saying ) that can assist with your Cloud Data & Analytics capability evolution and value realization.
Integress – The Data Analytics Company is a Philadelphia-based Data Analytics Company focused on helping clients figure out how to leverage their data to make real impacts to their top- and bottom-lines.