Building your modern data factory? 3 questions you need to consider

CA has become a trusted digital transformation partner for thousands of companies. What's next for these modern enterprises?

CA Technologies has become a trusted digital transformation partner for thousands of companies across many industries. What’s next for these modern enterprises?

CA Technologies Data & Analytics Team is proposing a course to navigate the uncharted path.

Whether you are well on your way to establishing your modern software factory, or are still in the planning stage, there is a simple question that remains: how do you make your data work (harder) for you?

Every application generates performance and usage data from statistics, to logs, topology, user journey maps and more. This information is invaluable. It can be used to optimize app performance, detect and predict issues, and notify you of outages and other unwelcome interruptions.

Whether you are focused on fixing day-to-day problems or planning for the long term success of your business, your data insights present a tremendous opportunity to get ahead of competition. Engineering a framework that runs analytics on a data stream produced by each of your applications, while resource and time consuming, is not an impossible task. There are open source components out there which could significantly reduce the cost of development. Best practices from thought leaders in the analytics space are publicly available. Additionally, many schools offer programs for Data Engineers, Data Scientists, and AI & ML applications developers; so the supply of qualified data professionals is certainly growing.

Alternatively, as part of your “data to insights” journey, you may consider a pre-built toolchain that’s deployed on top of an analytics framework – a viable option for time and resource constrained IT leaders. While advantageous, this route comes with its own set of challenges.

Let’s look at the top concerns the CA Technologies Data & Analytics Team hear when talking to customers.

Question #1: How do I avoid vendor lock in?

There are proprietary analytics applications in the market which, great at they may be, will lock you into a long-term maintenance contract with the vendor. Given the sensitive nature of the data, you may not be able to afford an interruption caused by transitioning platforms when your business needs a change. You may consider an open source-based solution, where most of the code comes from well-known, tried-and-trusted technologies such like Spark, Hadoop, Elasticsearch, Kafka etc. Your data model and formats can be easily replicated, regardless of the vendor.

Question #2: How do I get assurance that all my apps will work with my new analytics tool?

If experimenting with a new toolchain, look for ones native to the analytics framework you’re interested in. If a vendor is building their applications with the analytics component being a requirement, failure is not an option for them. Additionally, look for microservice-based tools, which support data-heavy integrations with a higher success rate. And finally, pay attention to key components, such as  visualization. Are the components solution native? Secure? Is your vendor of choice open to evolving these? Or simply provides these to you “as is”?

Question #3: How do I protect my data?

This question comes up a lot when building and deploying analytics-driven applications. What can you do to protect the terabytes of data likely traveling to your analytics engine each day? Do you lock it down on-premise and invest in an engineering workforce to maintain your data center? Do you go with the public cloud solutions and trust your vendors to have the right safeguards in place? Or, like most, do you create your own hybrid cloud and optimize as you go?  While there is no one-size-fits-all solution here, going with a solution from a trusted industry vendor, and accurately estimating your risk profile will help. Many customers “test the clouds” with a low risk application or two before going full force. Some prefer the security of an on-premise solution, but allow their encrypted data insights to be sent to the cloud for processing and visualization.

No matter which path you chose, with time and effort, you can transform your business into a data-driven Modern Software Factory. The one choice is whether to approach this challenge as another problem to solve, or as an opportunity to leave your competition in the dust.

To learn how we build data-savvy applications with CA Jarvis, email and visit

CA Community is the blog manager’s account used to post general updates and news items.


Modern Software Factory Hub

Your source for the tips, tools and insights to power your digital transformation.
Read more >
Low-Code Development: The Latest Killer Tool in the Agile Toolkit?What Are “Irresistible” APIs and Why Does Akamai's Kirsten Hunter Love Them?Persado's Assaf Baciu Is Engineering AI to Understand How You Feel