Exclusive Interview with JP Romero, Technical Manager at Kalypso

As data stores continue to grow, modern data governance programs should consider appropriate measures to keep up with the volume, whether it means leveraging automation and machine learning, expanding their data stewardship teams, or a combination of both. Kalypso is Rockwell Automation's digital services arm, which has comprehensive capabilities in consulting, data science, technology, Business Process Management, and managed services. Analytics Insight has engaged in an exclusive interview with JP Romero, Technical Manager at Kalypso.

1. Kindly brief us about the company, its specialization, and the services that your company offers.

Established in 2004, Kalypso is Rockwell Automation's digital services arm since 2020. Our services cover the full scope of innovation in the digital value chain. We have comprehensive capabilities in consulting, data science, technology, Business Process Management, and managed services.

2. Mention some of the awards, achievements, recognitions, and clients' feedback that you feel are notable and valuable for the company.

Kalypso has been recognized as a digital leader by Gartner, IDC, CRN, IoT Analytics, and as a PTC System Integrator Partner of the Year.

3. The advancement of data management technology has influenced customers on their current and future needs. Explain the challenges customers face to have the data management technology in place?

The world has come far from the days of running a few SQL queries from a cron job and calling it a Data Quality/Governance initiative. Data Management technology now allows entire organizations to align on where their data is, what it means, and whether it can be considered trustworthy or not. One of the most critical challenges is building a healthy data culture since true data democratization cannot happen without data literacy. Furthermore, as data stores continue to grow, modern data governance programs should consider appropriate measures to keep up with the volume, whether it means leveraging automation and machine learning, expanding their data stewardship teams, or a combination of both.

4. Which industry verticals are you currently focusing on? And what is your go-to market strategy for the same?

Kalypso focuses on three main verticals: Life Sciences, Consumer, and Industrial High Tech. Our go-to-market will have some overlap when applicable, but we always take an industry focus as this allows us to better understand and tailor-fit solutions for our clients. For example, when speaking of data management, many data challenges are shared across industries: an enormous amount of data, no clear data ownership, a lack of an enterprise data culture, and so on. However, a financial services client might be more concerned with federal regulations, so their main business driver to get data under control will be different than let's say a client in CPG or retail.

5. How can businesses efficiently extract the value from data, without increasing cost and complexity?

There is always going to be a cost to extracting value from data, however, you can prevent the cost from snowballing by making sure the enterprise first and foremost agrees to its meaning and its trustworthiness. We have seen it happen everywhere: two or more teams using the same data set, arriving at completely different (and sometimes opposing) insights. By investing in Data Management, businesses are protecting their machine learning and analytics initiatives. Otherwise, they would succumb to the adage: "Garbage in, garbage out".