2020 was a good year for analytics startups (to wit, Snowflake’s stunning IPO and strong funding news across the sector). So far, 2021 has been bountiful, too, with other startups achieving unicorn status and pulling in millions in total funding. Managed analytics solutions are hot, to put it mildly, and that’s great news for all of us in the ecosystem, especially enterprises who are ramping up their efforts to turn their data into revenue and market share.
Whether your organization wants to make its first foray in the data analytics arena or step up its game to improve cost and control, you’ll want to take into consideration the pros and cons of using managed analytics solutions.
The primary reason to go with a managed analytics service provider is speed—not speed of query, but rather speed of business. With the resources of a provider like Snowflake at your disposal, you can have an analytics program up and running in fraction of the time that it would take to create an in-house data operation. It’s a great way to get started.
Because cloud-based analytics solutions are managed externally, enterprises can avoid dealing with the in-house DevOps burden. Your internal IT team doesn’t need to manage or dole out the cloud resources to support analytics workloads, and that saves time and money in terms of both personnel and IT infrastructure.
Third-party analytics solutions give users unfettered access to their segmented subset of data. This is a powerful “pro” as organizations seek to empower more and more business units throughout the enterprise to capitalize on data. The more users that can apply insights from the organization’s data the better, and managed analytics solutions are happy to provide access to as many users as you wish.
So the big appeal of managed analytics services is that an enterprise can start using data analytics quickly and let their third-party provider deal with all the hassle of storing and managing the data. More importantly, users throughout the company can quickly run unlimited queries without having to wait on the DevOps team to allocate resources.
What’s not to love about that? Well, very little, really, unless you are hesitant to write blank checks.
Although the idea of democratizing your data and eliminating DevOps sounds great, there’s a catch. Managed analytics services operate primarily with one large control knob: as you turn the knob to the right to run more or faster queries, your monthly bill goes higher and higher. As adoption grows and users continue to throw unchecked queries at your service provider, your spending balloons.
The dream most organizations have about data analytics is to quickly and easily access any and all of the data they need, no matter its source, format or current location. In reality, most enterprises have multiple data stores of one kind or another—perhaps they use Snowflake, Redshift, or any number of other systems across clouds or on-premise. For a wide variety of reasons, the fantasy of pushing all that data to a single, third-party data warehouse never comes to fruition. Unfortunately, at the end of the day, every managed analytics solution becomes another data silo to manage its data flows. Conversely, a lower upfront DevOps investment can translate into more DataOps down the line.
With the cybersecurity and regulatory challenges enterprises face today, whether they are startups or multinational conglomerates, moving data into the possession and control of a third-party analytics provider breeds risk that most organizations would be wise to avoid. Unified access control, audit trails, data lineage, discovery and governance all become complex with managed services requiring custom integrations and vendor lock-in.
Should enterprises today be investing in Big Data and analytics to fuel smart business decisions? By all means, yes! The marketplace is ripe with exciting companies that are making innovative analytics solutions more accessible and easier to use than ever.
CIOs need to be aware of the pros and cons of “quick-start” managed solutions and be ready to shift to more economical in-house managed DataOps programs for the cost and control advantages they offer in the long term.
Schedule a short demo now to see Varada in action on your data set!