CEO Perspective: Future Trends in BI and Analytics
Keeping your data centrally accessible is the key to getting the most from it.
There’s nothing more central to successful BI than centralized data. We spoke to George Fraser, CEO and technical cofounder of Fivetran, who explains why this is so important, what technologies are important now, and what emerging technology you should be paying attention to.
What technology or methodology must be part of an enterprise’s data strategy if it wants to be competitive today?
George Fraser, You need to have a tool that centralizes your data into a single location. You’re not going to be able to do all the things that you want to do with your data unless you have it all centralized.
What one emerging technology are you most excited about and think has the greatest potential? What’s so special about this technology?
Data warehouses that separate compute from storage, such as Snowflake and BigQuery. These warehouses leverage the cloud in a fundamentally different way than earlier data warehouses. When you’re able to scale your compute up and down on demand, many of the problems that people had in the past with data warehouses, such as concurrency issues, just disappear. Professionals that spent 90 percent of their time working on data warehouse issues in the past can now spend their time on projects that drive value for the business. Everyone knows this technology is special, but it's even more special than people realize.
What is the single biggest challenge enterprises face today? How do most enterprises respond (and is it working)?
I think the single biggest challenge businesses -- not just enterprises -- face is hiring great talent. We’ve been in a ten-year economic boom and the job market is about as tight as it can get.
One thing that makes an organization a good place to work is transparency. A lot of people talk about using data to make better business decisions, which is important -- but there is a second benefit that relates directly to finding talent and hiring, which is that you can create transparency with data.
As an employer, you can ensure that everyone in your company across all departments and levels has access to the data being used to drive decisions. You can use data to create transparency so that everyone can understand what is going on in the business and why decisions are being made the way they are.
Your employees should be able to see whether the things they’re doing are working or contributing to the overall goals of the business. This can be achieved through data and data transparency.
Is there a new technology in data and analytics that is creating more challenges than most people realize? How should enterprises adjust their approach to it?
There are great new BI tools out there, such as Looker and Sigma Computing, as well as great new data warehouses, such as BigQuery and Snowflake, but I think what people sometimes don't realize is that these tools can't do anything about bringing the data into themselves. They give you a great environment to analyze your data, but they won't put the data in that environment. Although a lot of their marketing materials talk about getting all of your data in one place, they don’t actually solve that problem.
Getting your data together is difficult. Oftentimes companies end up deciding to put together their data warehouse and do the ETL with their own engineering team. They don't necessarily realize that they're signing up for a mammoth effort to centralize their data that is going to metastasize across the organization, consuming unthinkable amounts of time and resources.
Enterprises should adjust their approach by using ELT tools (which are different than ETL) that specifically solve for the data centralization problem.
Where do you see analytics and data management headed in 2019 and beyond? What’s just over the horizon that we haven’t heard much about yet?
I think we’re going to see a lot of the existing trends continue, including increased adoption of cloud data warehouses, which I think will become one of the dominant use cases of cloud computing. The main job of IT at a lot of traditional companies is data warehousing. As more and more traditional companies move to the cloud, we’re going to see data warehousing representing a growing percentage of what is being done in the cloud.
Something just over the horizon I find very interesting is Azure Data Explorer. It is basically a complete reconceptualization of the data warehouse, including a totally new query language that is fascinating. Although it has just recently become publicly available, I am told it has been widely adopted within Microsoft. I’m interested to see how it plays out because it is so ambitious.
Tell us about your product/solution and the problem it solves for enterprises.
Fivetran is a zero-configuration data pipeline that centralizes all your business data in your data warehouse. Centralizing your data is the hardest part of building an enterprise data warehouse, and we’ve built the only truly turnkey solution.
[Editor’s note: Fivetran’s George Fraser is notably involved in projects with strategic partners, customers, and external audiences where his technical expertise in analytics and data warehousing is valuable. You can reach the author via email or Twitter.]
James E. Powell is the editorial director of TDWI, including research reports, the Business Intelligence Journal, and Upside newsletter. You can contact him
via email here.