What is it that a Service Provider like Coforge can do to add value to the services we already provide to the customer? Can we ensure quicker ROI on customer’s investment in data? Can we provide something beyond expected software and service deliverables that help reduce data modernization cycle time without hitting customer’s IT budgets? Let’s try to find answers to these.
Starting with the build vs buy debate, we know that buying off-the-shelf software products can get business up and running fast and can be cost-efficient when compared to developing the entire software in-house. But as businesses start using these products, they realize that many of the cheaper off-the-shelf software is not scalable enough or that many of the business requirements are not supported and require heavy customizations. CTOs are then left with two options. Either they invest in premium software products or build the solution in-house. While in-house development offers a bespoke solution that perfectly satisfies business needs, time to develop is usually high and that spells higher development costs and time to market. This is where Coforge can make life easier for businesses with its data innovations.
Opportunity to innovate
While building data pipelines, implementing data governance solutions, and generally building solutions to implements in the entire lifecycle of data for our customers, we observed that there are a lot of common activities that all solutions need to perform. Hence, there are a lot of components of data management infrastructure that are similar across organizations and industries. This presented us with a great opportunity to innovate, which we gladly grabbed and prepared data innovations toolkits collectively known as the Data Studio.
A case for Data Studio
Data Studio comprises of re-usable software that hits the sweet spot between build and buys by providing customers with a cost-effective, low-code platform for the development of their data solutions. It allows us to accelerate the development of solutions without compromising on features requires by customers while protecting the customers from the potentially overbearing cost of premium products.
Introducing the Data Studio
Akin to Lego blocks that can be quickly put together to build a large model, these accelerators can be put together to create a cohesive data solution. Each of these innovations is mutually exclusive from others in its functionality. Yet, collectively, they are exhaustive enough to cover the entire data lifecycle.
Let us examine the various innovations that we offer and how they apply to the data lifecycle.
Data Acquisition and Processing
The very first stage of the data lifecycle is acquiring data from various sources. These could be on-premise, off-premise systems, legacy applications from where data is to be collected. flow press and MigXpress do the job of getting the data into the newly developed modern data system. IoTXpress caters to the growing need of acquiring data from a multitude of sensors.
Understanding the industry-wide adoption of large data lake systems, we have created specialized innovations in this field. In an on-premise or Cloud-based IaaS Data Lake, DLXpress smoothly creates the data pipelines, orchestrate the processing, and managing of the data lake. Similarly, for PaaS based Data Lake implementation on the Azure cloud platform, we can leverage Alpha Data Lake innovation to leverage Azure services to implement the Data Lake.
Once data has been processed, it can be analyzed by data scientists and data analysts to generate actionable insights. MLXpress allows the rapid creation of Machine Learning use cases. AlgoXpress provides a vast repository of Data Science algorithms to data scientists, while HackXpress allows collectively leveraging a team of data scientists to solve business problems. CogNIITo allows for exploration and analysis of raw unstructured data that is collected by a plethora of social media and unconventional data sources.
Once data is all processed, analyzed, and ready for consumption, we can leverage VizXpress to migrate reports from legacy reporting platforms to the latest reporting technologies.
In an increasingly digitized world where data is the new currency, our Data Meter innovation enables accounting on that currency by keeping a track of data consumption on a Data Virtualization platform.
Last but not the least, while all that is discussed above is happening, we are dealing with a huge number of external data sources as well as internal data stores. This necessitates keeping a track of data sources, establishing the lineage, understanding the metadata, and the relationships between different data entities and elements. All this is made enabled by the MetaXpress tool.
Along with an understanding of data, we need to ensure that data hygiene is maintained. DQXpress allows us to ascertain and maintain the quality of data by allowing the creation of data quality checks and quality remediation processes. DTXpress on the other hand allows us to validate that the data in the system is as per the business expectations.
And finally, beware of the trap
While considering and evaluating all these innovations for deployment in a data system, we need to avoid the trap of comparing these with premium commercial products. These innovations are not meant to compete with commercial products. Those products are created with a different objective altogether, which is to obliviate the need for a bespoke solution. Our innovations, on the other hand, aim to accelerate the development of bespoke solutions by providing low-code development platforms.
We at Coforge understand that frugal innovation is a continuous journey and we take great joy in undertaking this journey to give the very best of data solution to our customers.