I had the privilege of sitting down in a one-on-one interview to talk with the founder and CEO of Gathi Analytics, boutique Enterprise Data Firm based in Dublin, OH. After speaking with Vamsi, it’s clear why Gathi is seeing exponential growth year-over-year. Here’s a look, from Vamsi’s perspective, about what makes his company unique and how they’re tackling the Data Analytics Industry’s toughest problems.
At Gathi Analytics we see ourselves as strategic partners and an extended team of our enterprise customers. We typically work with CIOs, Chief Data Officers, and Business Executives to understand the challenges and opportunities that exist in their data and business domain.—Vamsi Kora, CEO, Gathi Analytics
Getting Started with Gathi
We conduct initial assessment and through our strategic consulting, deliver data transformation roadmaps enabled with tech modernization and architecture, identify data optimization opportunities, and, most importantly, the inherent value that exists within enterprise data and how organizations can leverage them seamlessly, effectively, faster. We generate data insights and identify how those data insights can really enhance and expand business operations through reduction in customer churn and improving monetizable data assets.
Our experience with mid-sized banks, health care operations centers, retail companies, or government organizations shows huge investment (both money and effort) in building enterprise data assets in last 15–20 years. These assets deliver specific value to the business but not always at the speed and the quality that the business needs for today’s operations. The need to keep up with regulatory compliance while also keeping cost in check, are often challenged by the overhead of managing diverse legacy platforms.
The Rise of Data Modernization
Fortunately, the industry is realizing the true cost of owning, managing, and maintaining disparate, legacy data systems. Most of the senior leaders we work with are extremely aware of both the challenges and the opportunities that exist within their data assets. So, we partner with them and we help them to enhance their thought process, deliver highly actionable and highly business-value-driven data roadmaps, and execute on them.
One of the key factors of these data roadmaps is we build program plans that deliver specific business value every three to five months. We don’t believe in long years of investment that go nowhere and don’t really excite business partners within a company. We are very mindful of how we can deliver incremental value every three to five months and how that helps business in a very tangible way. This includes every aspect of making enterprise transactional data an information asset for the company.
Two Ways to Tackle Data Modernization
At Gathi, we have a two flavors of service offerings that we have built on what we call a “modern data platform” — the services suite and the metadata service layer — both of which are built on open-source technology. These services align very neatly on both AWS and Azure Cloud platforms as well as on on-prem platforms. These services act as extreme accelerators for data modernization efforts and data transformation optimization programs — converting existing data sets into data as a service, analytics as a service, with an information gateway as a delivery mechanism.
What Sets Gathi Apart
We leverage our 20+ years of experience in delivering extremely large heterogeneous, highly complex data assets for large corporations, and strictly focus on the ultimate value that should come out of your data assets. We’ve built a data analyst view of how design and development should happen. We’ve also built a data modeler’s view on very comprehensive metadata and data architecture. Additionally, we’ve added a developer’s view focused on the speed in which they can deliver quality code to production.
In the marketplace, there are hundreds of products that deliver specific functions of data management — data profiling, data cleansing, data access, metadata, data integration, data processing etc.
With this in mind, we designed our suite of services to address our customer’s critical data needs in one platform, available on day one of our engagement. We’ve coupled these services with a delivery framework — providing a clear roadmap to take our clients from current state to target state. One by one, we breakdown key milestones required to deliver reliable data at scale. Once the framework and services are in place, we have all the room we need to run at full speed — delivering continuous innovation throughout our partnership.
Real Results in a Few Short Weeks
Recently, we delivered a marketing analytics platform for one of our customers in the insurance industry in less than 16 weeks — designed and developed. This speed is what our customers are really appreciating. We are getting more traction as more companies are saying speed is a critical factor when converting their segmented, disparate data assets (with inconsistent data quality) into actionable insights. Achieving all of this in a matter of a few months makes a significant difference to the bottom line.
The Price of Not Changing
In the data industry, we keep talking about ‘The Price of Not Changing’. This price comes when organizations don’t make the investment in data modernization.
There are a number of reasons why this investment is critical. Organizations are trying to adapt to aggressively changing consumer behavior. As customers, we all want everything at our fingertips, through our phones. When we pay a fee, we want that reflected instantly on our statement. This type of expectation has driven a lot of digital platform modernization in the last few years. However, no business or digital modernization program will be successful without a very robust and highly dependable data platform that is providing high-quality data at scale and on demand.
Moreover, data assets are piling up and managing them has become one of the most expensive items for CIOs or CFOs — and year over year, this cost is growing. Velocity, variety, and volume are three things that continue to increase data costs. Data quality has become a huge problem for companies — especially in financial sector. Poor data quality results in disorganized and undependable data. Not to mention the very expensive manual efforts to respond to regulatory demands.
The goal is to reduce overall cost while taking advantage of the benefits of having high volume, high velocity data. Especially when organizations look to leverage new technology and move away from highly siloed data structures. Getting this transformation right means the difference between success and failure for many years to come. Of course, it can also mean millions saved (or lost) if not executed properly.
The key to achieving this goal is simple — Gathi delivers enterprise data programs leveraging the right combination of experienced architects and cloud-based accelerators. —Vamsi Kora, CEO and Founder, Gathi Analytics