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Data Is the New Oil… or Is It?

At Skeddly we’re focused on bringing you the best in AWS help tutorials, AWS scheduler services, and AWS backup services. However, from time to time we like to reach out to other leaders in the AWS space to help you, our blog readers, stay on top of the latest developments and news within the AWS ecosystem.

Today Skeddly had the opportunity to speak with Remy Rosenbaum, VP, Marketing & Analytics at Caserta, a big data and analytics company that helps businesses harness the power data to exceed their business goals.

Without further ado, let’s jump into the interview.

The Interview

Hello and thank you for joining us at Skeddly today to talk about Caserta. You help leaders do amazing things with data. Can you kick off this interview by telling us about what some of those amazing things are?

At Caserta we’re helping leaders use data to drive their goals. We’re helping one client of ours to use data in the fight against Cancer. By using personalized cancer treatment based on data-driven mathematical models, they are able to both improve the chances of cancer going into remission and improving the lives of patients during treatment. Data is at the core of using less medicine in a more precise and far more effective way, while minimizing dangerous side effects. Using data from many different sources is a huge challenge in and of itself. The data comes in different formats and types and sources and it is difficult to leverage the data and put it to use in a quick and efficient way. We’re helping this client go from one-size-fits-all medicine to precision personalized medicine, by combining many different data sources including genomic data, IoT data, medical records, compliance and exogenous factors. This is a truly amazing feat.

Now before we jump in and talk about the value of data, let’s first talk a little bit about technology and architecture. In one of your videos you talk about how some of the projects that you work on are cloud agnostic. Can you begin by telling us a little bit more about how you approach picking the right cloud solution for your clients who are primarily concerned with data analytics? Is one cloud solution better with data and AI over the others? What solutions are making interesting advances in the data and AI space?

One of the hallmarks of Caserta is that we are completely vendor agnostic. Our clients trust us to choose the best platform and technology stack for their unique business needs. Typically all the major cloud vendors have comparable solutions, but there are other factors involved. Some verticals, such as retail, prefer to stay away from AWS as they view it as a direct competitor. Other clients are traditional Microsoft shops, and it would make the most sense to use Azure. We will always make sure that each client has the technology that not only helps them to achieve their business goals, but also future-proofs their business beyond their immediate goals.

I watched the keynote by Joe Caserta about the value of data and was really inspired by the conversation. You work with companies in a wide array of industries ranging from media companies like New York Times to financial service companies, higher education companies, retail companies and even non-profit organizations. Can you tell us a bit more about what some common objectives are when it comes to making data valuable within an organization? These companies are looking for data to help provide direction, so what are some common things companies across industries are looking for? Can you give us some examples?

Data analytics has evolved. At its most basic, people across industries would want to know what happened. This could be what sales were, what geographies were strong etc. This is called Descriptive Analytics and almost all businesses use this. Then for organizations, the question becomes why something happened. This is Diagnostic Analytics and aims to identify correlations in order to try and explain business and glean insights. After that the questions evolve to “what will happen,” to “how can we make it happen.” Most clients are working towards those goals. The last step would be self-learning analytics, which would be AI-driven self-learning analytics, which would be able to learn on the fly and interact with the customers or make automatic business decisions. We have clients at every step of the way and help them become more data-driven to achieve their goals.

Beyond providing directional guides, the data can also be valuable in other ways. For example, companies can sell their data. In these cases, why would one company’s data be valuable to another? Can you give us examples?

On the consumption side, the world of Alternative Data is a great example. This is data that is gleaned from “alternative” sources and sold to third parties in order to make high-value business decisions. Data of this type can come from web scraping, satellite data, even arial photography. We’ve helped many clients across different verticals including financial services, insurance and transportation, build out alternative data platforms in order to consume this data and leverage it for business. To help clients value and monetize their data, Caserta has built a practice around data monetization. We have brought on Doug Laney, the “Father of Infonomics”, as Caserta’s principal data and analytics strategist. Infonomics is an enterprise data management concept that Mr. Laney coined in his best-selling book of the same name for valuing and accounting for data/information as a real-world asset.

On the flip side of this coin, companies may also choose to purchase data. Can you tell us a little bit more about the logic behind companies who decide to take this approach? Is it simply because it would be challenging for them to acquire the data themselves? Can you tell us what some common reasons people buy data for (i.e. customer behavior, buying trends etc)?

Build vs. buy is always a consideration for companies. This applies not only to the data itself but also to technology stacks and analytics platforms. Price is not always the main consideration, rather availability. The data a client is seeking is not always available on third-party data markets, or there may be problems with the veracity of the data. Other technology issues, such as schema shift, also need to be taken into consideration when purchasing data. Caserta helps to vet data sources and work through whether a company should source or purchase their own data. One prime example would be a private equity client that we helped build an alternative data platform with data gleaned from web scraping.

Is the market for buying and selling data a formal market? How do these transactions take place? How do data buyers and sellers find each other?

The alternative data market is massive. Many of these transactions take place via providers like Quandl or EagleAlpha. They can even directly purchase the sources. A great list of them can be found on As Caserta is vendor agnostic, we work with all data providers and data sources. Our clients are always first priority and we thoroughly vet any recommendations we provide. Like I mentioned before, there are always architectural and technological considerations when purchasing and integrating third-party data sources.

You also mention that you believe data is more valuable than oil because it has the potential to grow exponentially. What do you mean by this?

I tend not to like metaphors like these like “data is the new bacon,” or “data is the new oil” I think it only serves to confuse people about what data really is. But if we have to compare, data will be far more valuable than oil for a number of reasons. Data is not the new oil because data is non-depleting, non-rivalrous, regenerative, easily transported, cheap to store, easy to steal, and it doesn’t degrade. Also, unlike oil, it’s impossible to clean up if you spill it.

You believe that technology and the data itself really isn’t a problem anymore. If data isn’t working for a company, it’s likely not an issue with the data, but the people standing around the data. How big of an issue is this and how do you deal with overcoming objections to change or disruptions within the companies you work with?

People are larger obstacles than technology in the journey to become more data-driven. This issue is prevalent in every industry and shared by organizations large and small. People feel threatened by innovation and resist change. These fears include concern over job security, fear of inability to cope with new technology, status and perks under threat and more. The best way to combat these forces resisting change is by including a change management strategy into a data analytics project. If a data and analytics project does not have wide-spread internal adoption, ultimately it will fail. We work with our clients to implement an inclusive change management strategy that includes “reskilling” the necessary people.

You work with a lot of enterprise level clients on big projects. But how can data be efficiently used and incorporated into the decision making process for smaller companies and startups? What actionable tips would you give to companies who might not have the resources yet to hire a full time dataologist, but who still want to harness the power of data to help them achieve their business goals. How do you suggest they take their first steps into the world of data?

We work with companies large and small and have a number of start up clients that we have helped extract value from data to drive their business. The first step is clearly defining business goals. What is a client trying to achieve with the data? After goals are identified, you can then identify opportunities with the data. Cloud platforms have greatly lowered the barrier to entry for start-ups and smaller businesses. These allow businesses to bolt together various cloud technologies and have both storage and compute in the cloud. All the major cloud provides unlock the door to AI/ML with easy-to-use libraries that start-ups can access at relatively low costs. For best practices around cloud architectures, however, I would recommend speaking to an expert consultant like Caserta.

Thank you greatly for taking the time to do this interview and share your thoughts with Skeddly’s blog readers today. We truly appreciate your time. To our audience, if you’re interested in learning more about Caserta, you can follow them on Twitter or head over to their website here.

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