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It Takes a Village to Raise a Cloud Analytics Platform

May 13, 2021

As a person passionate about technology and working to help customers better deliver on their mission goals, I spend a lot of time thinking about patterns across the myriad of customers I’m fortunate enough to meet and work with on projects. I’m continually learning, assessing and working to understand things and as I come across new information and ideas on this never-ending technology journey I often assimilate those learnings to anecdotes and analogies from other areas of life.

Recently I had a funny, yet – very true thought: The African proverb “It takes a village to raise a child” is one that can be directly applicable to those of us actually raising kids, yet also can apply directly to the modernization efforts we’re seeing across government agencies working to modernize and improve their analytics efforts with cloud-native analytics platforms.

Confused?  Let me explain.

The concept of the phase is simple: parents will birth children into this world, but the path through life for their children will continually evolve and they will learn and be massively influenced by those around them (the village). Families should accept and reciprocate this responsibility to other children in the village. Ultimately; people must work together for the benefit of everyone (and their children) if they want to have a future.

This concept directly applies to many things in business and in life, yet is especially apropos to the current public sector paradigm shift where agencies are actively working to field cloud-native, shared service data analytics platforms in support of organization-wide modernization efforts to improve mission outcomes.

Successful innovators leading the charge across the public sector are all choosing a similar approach:

Building open architecture, cloud-native analytics platforms that integrate best-of-breed commercial technologies in an integrated, API-driven design that supports a variety of analytics needs for a myriad of business and technical users and use cases across the organization.

Inherently, agencies are building these platforms to empower users to operationalize data quickly to address specific analytics needs in a self-service-oriented design that improves time-to-insight by breaking down data silos and enables rapid advancement of analytics modernization efforts.

By leveraging cloud-based architectures and best-of-breed commercial products in an open and modular design, agencies are able to quickly field deep capabilities for different functional capabilities required by their user communities and actually attract users to these shared-service platforms.

This API-based design approach not only provides agility for the platform builders to plug-in new innovative platform features based on demand, but also reduces the risk of vendor lock by commoditizing basic cloud services like storage and compute. It also ensures continued innovation where capabilities across the platform can be iteratively improved as the DataOps tool landscape evolves along with changing user needs for emerging technologies.

Ultimately, for anyone working on fielding a cloud-based analytics platform, it’s critical to understand that the technology vendor landscape has evolved rapidly in the last decade. There is no longer any single technology vendor offering the depth and breadth of data management and processing capabilities required to meet the diverse needs of the analytics-focused, modern enterprise.

Today there are highly specialized technology vendors offering deep capabilities in certain functional areas with API-first product designs that can be interoperably deployed in cloud-native architectures. This not only provides flexibility and choice for organizations building their “‘modern stack” analytics architectures, but also ensures continual innovation as product vendors are continuing to provide a depth of new features to keep up with the rapidly evolving demands of their customers, while outpacing their competition.

Note:  We wrote a white paper on this shift a while ago, and over the last year, more and more programs are following suit.

For Trifacta, we’ve proven our value as the leader in data preparation, we also recently announced the industry’s first data engineering cloud. We’ve also been broadly validated across the public sector by being chosen continually for these cloud-based, shared-service-analytics-platform projects. A big reason for this is our API-first, cloud-native, extensible and low-code/no-code based product design, as well as our technology partnerships across the ecosystem of DataOps tool vendors. The Public Sector vertical is one of our fastest growing business areas worldwide. This tells me that agencies across the space are expediting their use of advanced analytics and modernizing rapidly to meet user demand.

Currently, we’re working with the US Air Force, US Navy, the Dept. of Defense, the FBI, the CDC, HHS, State of Maryland and numerous other public sector customers on similar analytics projects. And while Trifacta’s technology is a key functionality and chosen often by Municipal Government, Federal/Civilian, DoD, Health and Intelligence customers alike, we have strong relationships with many other commercial software vendors in the space and are continuing to invest and enhance those partnerships.

Trifacta has close alliances and cosell agreements with all of the major cloud vendors – Google, Azure and AWS.  We work closely with a number of key technology partners across the public sector that provide complementary capabilities in numerous projects for key functional areas including data visualization (Tableau, Qlik), data governance and accessibility (Immuta), data movement (Streamsets), text analytics (BasisTech’s Rosette), data platform/processing (Databricks, Snowflake, IBM) and data catalogs (Collibra, Alation).

Ultimately, while innovation is critical, it must be balanced in a risk-managed way so public sector programs can bring in cutting-edge tech and ensure it will succeed at scale.  All of these partners we see regularly across the public sector are leaders in their respective technology spaces and have invested in the public sector market, setting up teams to support the unique needs and requirements of customer agencies. They have also invested in each other, roadmapping functionality to ensure interoperability as part of overall analytics solutions.

As this paradigm is continuing to take hold rapidly across public sector agencies: Any architect, CTO or project leader working on solutioning should be making technology decisions with consideration on the technology itself, but also the commitment of your vendor partners to the space and to each other. This will ensure your investment will succeed and be supported long term while providing a foundation for interoperable innovation as your needs evolve.  Because, it takes a village to raise a cloud analytics platform.