Fivetran specializes in automated data integration and making data access as reliable & simple as turning on electricity

CXOToday has engaged in an exclusive interview with Mr. Viswanath C, Sr. Director of Engineering, Fivetran India


  1. Please provide a brief overview of the company, its areas of expertise, and its services.

Fivetran is a data integration company with a mission to support businesses through data-driven decision-making. With the boom in public cloud services, insufficient data is no longer the issue for enterprises. Instead, it is about having complete visibility, cutting through silos to have timely access of all data residing across the organisation’s data ecosystem.

This is where our expertise in developing simple and reliable data pipelines, or connectors, comes in. Instead of building custom pipelines to various apps, platforms, and other software, data teams can select from over 150+ ready-to-use connectors from our engineering teams. With zero configuration needed, the seamless setup process takes five minutes instead of the usual days or even months. Data engineers can reallocate their efforts towards data preparation and deliver insights to decision-makers in the shortest times possible.


2. How does Fivetran is making access to data as simple as turning on a switch for electricity?

The traditional process of extracting data is time consuming, reducing the timeliness of the actual data, the relevance of derived insights, all while increasing costs in both working hours and other expenditures. Data teams spend days, weeks, and even months developing customised connectors to different apps, platforms, and other software. More time and costs are expended updating these pipelines whenever an external data source is upgraded or modified in any way.

Fivetran allows businesses to scale data culture with our ready-to-use connectors that allow data to be moved daily, hourly or even every few seconds. With their zero-configuration setup processes, companies can better identify bottlenecks in the face of growing data needs. In addition, these pipelines automatically adjust to changes in data sources, freeing data teams for other, critical projects.


3. What are the key sectors according to you that are driving data transformation in India?

The tremendous growth in public cloud usage in India is propelling data transformation in the country. According to IDC, the local public cloud services market will have a CAGR of 23.1 percent until 2026, with manufacturing and banking services and financial institutions (BFSI) leading the way.

Data transformation is particularly crucial in the BFSI sector with a robust fintech sector and a corresponding wealth of data available for analytics purposes. For example, FIs are turning to non-traditional data points for alternative methods of developing credit profiles and personalising financial products. This can enable institutions to reach potential customers that are not serviced by their competitors, resulting in increased market penetration.


4. What are the main driving forces behind India’s data growth, and what role does big data play in the Indian business landscape?

India’s digital economy exceeds many other countries in terms of both volume and growth. The increase in Internet connectivity, along with the growth of smartphone penetration, are two major driving forces behind India’s data growth and an overall acceleration of digital transformation for both enterprises and the public sector.

When properly leveraged, big data can provide Indian businesses with a host of competitive advantages. These range from making internal processes more efficient, developing more customised products and customer experiences, forecasting potentially disruptive events, and everything in between. At the heart of this is being aware of all the available data in your enterprise’s cloud ecosystem, having timely access to all of it, and leveraging the right tools to distill insights from said data.

Easy-to-setup, zero-maintenance data pipelines ensures more time spent deriving insights from data. Teams will be spared from losing weeks and months to complicated configurations or modifying connectors during systems or external app updates.


5. What are some of the industry trends to look out for in 2023?

Solutions providers will be looking to provide better products as more businesses are turning to machine learning and analytics to be competitive. We expect more innovations in terms of data streaming latency, the emergence of “data lakehouses”, and continued interoperability within the modern data stack.

Having real-time data infrastructure currently entails enormous financial, manpower, and workhour costs. Businesses will be looking to drive down these expenses as more and more competitors utilise machine learning.

Meanwhile, the demand for a single, unified data architecture that has the best features of both lakes and warehouses will give rise to “data lakehouses”. This will enable users such as data scientists with access to large amounts of raw data necessary for ML, while giving processed data for the likes of business analysts to present to executives and decision-makers.

Lastly, interoperability between different data stack tools is here to stay due to open source software and open standards. Organisations see vendor lock-in as an impediment to innovation and solutions providders are following suit. For example, there are already tools that allow users to link any processing tool or query engine with their data lakes and warehouses.


6. How does Fivetran see India as a market moving forward and growth plans?

We have made great strides in India, both as a market and as a base, since 2017. As a market, we have doubled our customers and achieved USD 1 million in annual recurring revenue since the official launch of our product offerings in January 2021.We are now looking to provide a broader range of high-performing data solutions to customers across India through the launch of a new local AWS data centre. We have also acquired HVR, a leader in the field of enterprise database replication.

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