As businesses grow, their data load increases significantly, making data management a priority for any organization. Data management can include cloud and on-premises data storage, a data security strategy, and protection of data and assets.
New York-based CI&T, an end-to-end digital transformation company, offers data management technology as part of its IT security management line.
Datamation interviewed Young Pham, chief strategy officer at CI&T, who shared his perspective on the development and growth of the data management market.
For more information, also see: Data Management Platforms
About Young Pham
Young Pham is CI&T’s chief strategy officer and an expert in business development, strategic planning, organizational management, product development, marketing, and research and analytics. Pham graduated from Texas A&M University with a degree in business administration and has worked for CI&T since 2017.
Interview: Data Management
How did you first start working in the data management market?
I started my career as a database manager (DBM) at the start of the dot-com gold rush. One of the original platforms that I worked on included FoxPro, a text-based object-oriented programming language, among other traditional database management systems. A far cry from where we are nowadays with modern data capabilities.
What is your favorite thing about working at CI&T?
CI&T’s company culture is rooted in continual experimentation and improvement. This is great because we work in a really dynamic environment where we are always adapting and working to discover better solutions for continuous innovation both from an organizational structure standpoint and for our clients.
What sets CI&T’s data management approach or solutions apart from the competition?
For us, it’s about treating data as a product that can help empower organizations to optimize and/or do more. Data products with rich feature sets are central to a data strategy for driving measurable business benefits.
For our approach, we don’t start out with technology solutions which won’t necessarily have any impact without looking at the overall operational model first. Instead, we focus on what outcome we’re trying to achieve. We then work backwards, teaching our clients how to collect and utilize the data at their fingertips.
For us, every client’s needs are also different. The CI&T data journey is unique to and customized for each business so that a data strategy is tailored to fit the company’s reality.
For more information, also see: What is Big Data Analysis
The Data Management Market
What is one key data management technology that particularly interests you?
We’re currently doing a lot of our work with Drift, which organizes technology with respect to industry verticals. Data capabilities are often the same or similar per industry. For example, data in the retail industry is largely the same, as is data in banking and so on.
So having previous business use cases at our disposal limits the time and effort required to gain background, meaning we can get right to the work on the operation model as it pertains to a specific business.
What is one data management technique that teams should implement?
Data observability and monitoring can help teams quickly identify when something is off in their data, which can be crucial for a business. With monitoring implemented, it is easy to pinpoint if there are issues with data ingestion, for example, which relies on freshness and accuracy.
A complete observability solution would also take into consideration data quality, volume, distribution, and lineage. To be even more proactive, you can set up alerts to support your dashboard and trigger warnings in the main communication channel.
What is one data management strategy that companies should implement?
Data governance and documentation. Most companies struggle to know what kind of data they own. We have seen companies focus on storing data but with no real familiarity with it.
Creating documentation such as a data catalog is essential to have a clear view of the data available. Having a defined strategy around data governance helps extract the most potential from it since companies need to understand the topic from both a technical perspective (how your data relates with each order) and business perspective (what that data represents for your business).
What is the biggest data management mistake you see enterprises making?
Throwing money at tech. The data market is expected to grow 11% CAGR (compound annual growth rate) for the next 5+ years, which is significant spending already. I think replatforming or throwing money on the technical solutions without having a strong operational model does not make effective use of data capabilities.
This includes having data governance, a data product mindset, and data literacy.
What are some current trends in the data management market that are promising?
Data mesh — a modernization of the old monolithic data lake, where components can now be decentralized to those closest to the data. At CI&T, we’re huge proponents of “data as a product,” and for this to happen, we need data mesh as a way to get these data products distributed.
Data governance — again on my soapbox of “data as a product,” we believe that without data governance, there’s a limit on how IT and businesses access and use data effectively. Where does the data come from? How, where, and by whom was it processed? Data quality analysis is sometimes overlooked, but it’s another crucial step on the journey.
Data automation — facets like data management, cleansing, and data quality are going to be more automated to increase efficiency.
What are the biggest factors that are driving change in data management?
That would be AI (artificial intelligence). In the past, data management and ensuring data quality was a manual task. Using AI, we’re able to identify, reduce duplication, and make more efficient use of data. We talk about automation, but AI to support this is one of the biggest factors that we see driving change.
How has data management changed during your time in the market?
What’s interesting is that the technology has substantially improved over the years. However, I think the operational models and governance within organizations hasn’t really kept up. Teams aren’t getting the full value out of data management, and I don’t think that’s changed at all in the past 10–15 years.
Where do you predict the data management market will be 5 or 10 years from now?
I think with automation, a lot of the workflow management with data will be significantly easier and more streamlined. And with that, data strategies and insights will improve as well, making data even more valuable.
For more information, also see: Top Data Analytics Tools
Personnel in Data Management
If you could give one piece of advice to a data management professional in the beginning of their career, what would it be?
Learn the soft skills as much as the technical skills. When we say soft skills, that includes how you communicate your ideas to teams, how to influence stakeholders, how to really understand customer needs. Effective communication and being able to bridge the gap between the data and its meaning lends to being a successful data management professional.
With the shortage of tech talent, how is your team finding and retaining professionals to work in data management?
CI&T has a global footprint supporting multinational companies for over 25 years. As a digitally native company, remote work and virtual teams have been in our company lexicon well before the pandemic changed the working landscape. We find data professionals where they are, including Canada, the Continental U.S., LATAM, Asia-Pacific, Europe, and Northern Africa.
In terms of retention, I think our culture of experimentation and empowering our teams to continue to evolve our capabilities, looking at new technologies, and addressing the operating model makes CI&T a place where data professionals want to be.
For the greatest business impact, what should cloud storage professionals be focusing on most in their roles?
FinOps, or cloud finance operations, which allows organizations to get the maximum business value from cloud by helping technology, finance, and business teams collaborate on data-driven spending decisions.
A big part of that includes the data loads and whether or not the costs for cloud natives versus hybrid on-premises solutions are the best fit for organizations. It’s important for cloud storage professionals to understand how to maximize those data loads to costs as well as to performance.
For more information, also see: Top Data Warehouse Tools
What is one of your top professional accomplishments?
I would say it’s less of an accomplishment but rather a learning lesson based on falling down and being resilient enough to stand back up. I was in the middle of the dot-com days when everything we did seemed genius. I was also in banking when the 2008 collapse happened. What I learned is resilience — and that you’re allowed to challenge ideas whether or not the thinking is “group think” or actually something smart.
What is your favorite part of working in the data management market?
It’s the problem-solving aspect of my job. Data solutions are relatively the same. The unique application of that to a client’s specific needs is problem solving.
What is one of your favorite parts of the work week? How does it encourage or inspire you?
It’s always the end of the week — I’ve either accomplished what I set out to do or I did not. Either way, Friday is not just the bridge to the weekend but my day to check in to see what I’ve accomplished that week and inspire me to tackle the goals for the week ahead.
What are your favorite hobbies or ways to spend time outside of work?
BBQ. I’m from Texas, so smoked meats and BBQ are a year-round event for me.
For more information, also see: The Data Analytics Job Market