The data space today is one of significant fragmentation. We moved away from the original behemoth platforms we all cut our teeth on in search of best-in-class tools that could give us exactly what we wanted. But do our systems now lack true integration because of so many specialized tools and the experts required to oversee them?
My guest this week thinks so. I had a fascinating conversation on the Data-Driven Leadership podcast with Tarush Aggarwal, founder and CEO of 5X, a modular, customizable end-to-end data management platform. We talked about the evolution of data analysis, the rise of the data generalist, and how organizations can benefit from a more holistic approach.
The need for a big-picture view of data management
When organizations rely on small, specialized tools for different data management needs, they get the best-in-class solutions they’re after, but there can be drawbacks. Managing multiple vendors and tools requires equally specialized team members to oversee, maintain, and optimize tool utilization. When those team members focus on only their own slice of the pie, they can miss that their tool has overlapping features with another, and the chances for multiple sources of “truth” are higher.
Tarush says a customizable end-to-end data platform lets organizations manage infrastructure holistically. This approach streamlines operations, allows organizations to achieve cost-effectiveness, improves data trustworthiness, eliminates redundancies, and ensures a cohesive analysis process from data ingestion to model building and reporting.
The power of the data generalist
Tarush talked about the need for data generalists—individuals who possess a diverse skill set and can handle multiple aspects of data analysis. Their ability to ingest data, build models, create BI dashboards, and push data back into other sources allows for a comprehensive and insightful analysis. Rather than relying on a large data team with dedicated roles, organizations can benefit from having agile and versatile professionals capable of managing various data tasks and aligning data strategies with business outcomes.
To prevent being left behind, companies must assess their tools, people, and processes regularly to ensure they are maximizing their potential and driving meaningful results. As business and data analysis continue to evolve, focusing on ROI and staying adaptable will help organizations make informed decisions to meet their unique requirements. Check out the full episode of Data Driven Leadership here.