DataSwitch: A No-Code Data Transformation Platform Making Cloud Data Migration & Engineering Simple & Fast
An on-premise system incurs high security and operational costs, lacks scalability, and has limited storage. In order to stay ahead of their competitors, enterprises from around the globe have already started moving from legacy systems to cloud data services to derive deeper insights about their business and customers.
However, some enterprises, especially the regulated segments such as the government and banking sectors, are still critical about migrating tothe cloud. Their concern is fairly simple: Cloud Data Engineering technologies are constantly evolving and keeping up with the change becomes quite difficult for regulated segments. Yet another difficulty that enterprises face while migrating to the cloud is with data governance.
Also, there is a rising necessity for self-service data engineering platforms in business segments within these enterprises that are often dependent on IT to drive data engineering. There is a lot of information lost during transmissions from Business to IT and vice-versa, resulting in conflict, error, and further delay.
What makes it even more tedious is that Cloud Data Engineering calls for niche experts, who are difficult to find. Gartner reports that over 87% of organizations have low analytics maturity and business intelligence to perform such bulky data migrations and integrations. The time and effort required to migrate and build solutions and the time to market are deemed to be high when done manually with human dependency.
In such a scenario, there are two options for an organization to venture into: they can either create a team of data engineers and scientists, who will build procedures and systems to generate insights and migrate the data to the cloud, or they can outsource the work to systems integrator partners. However, in both cases, enterprises will have to invest a significant amount of time, effort, and money to bring the data together and make sense of it, which is bound to keep piling.
DataSwitch, a Chicago-based Digital Data Modernization firm, is on a mission to help simplify an enterprise’s endeavor to transform data to modern cloud platforms and improve the generation of insights from the data, irrespective of how and where the data resides. Even better, all of it will be done without the need to code!
"We are reshaping the data science world with our unique and game-changing no-code platform that is a DIY toolkit for cloud data management to further enable enterprises for digital data transformation,” says Karthikeyan Viswanathan, Co-Founder & President of DataSwitch. “The significant level of automation that DataSwitch offers makes your digital data transformation exponentially faster and saves millions of dollars!” he added. This AI-driven Data Transformation Platform helps modernize enterprises that use outdated technology to compete with digitally savvy organizations cost-effectively and accelerate their data transformation initiatives with quality code.
How exactly does DataSwitch help?
DataSwitch covers the ecosystem of cloud data engineering, where enterprises can use this platform for data modeling, data integration and migration, data preparation and enrichment, and data consumption. DataSwitch makes the data engineering process more agile and faster by providing a self-service-based approach to drive migration or integration on the tech-stack of your choice- including Spark, DataBricks, Matillion, Snowflake, RedShift, etc.
With DataSwitch even tech-savvy business analysts can build data integrations on their own and easily pass them onto the IT teams to productionize, thus saving time and effort significantly, while reducing friction. DataSwitch increases accuracy up to 10x and also reduces the time to market. It takes care of the implementation of best practices without having to depend on experts. So, even IT teams within an enterprise can use DataSwitch without having to invest heavily in on-boarding niche talent.
Let’s dig a little deeper.
DataSwitch comes with three individual components: DS Migrate, DS Integrate, and DS Democratize.
To begin the transformation journey, DataSwitch's DS Migrate toolkit, a completely automated solution, migrates the data warehouse data, schema, and ETL code from the legacy data platforms like Oracle, Teradata, Netezza, Informatica, SSIS, DataStage, etc., into the target cloud platform of your choice. DataSwitch works with a vast range of modern cloud data platforms including AWS RedShift, Snowflake, Google BigQuery, DataBricks, Spark, etc. You name it, DataSwitch has got it!
We are reshaping the data science world with our unique and game-changing no-code platform for digital data transformation
Once connected to the enterprise’s ecosystem, the tool performs reverse engineering to understand the old data warehouse schema and ETL code, and then forward engineers the enterprise’s new design and cloud data model. DataSwitch makes it all simple with a natural self-service approach involving an interactive drag-drop UI. This sets the stage for a modern cloud data platform, where the enrichment process begins.
DS Integrate toolkit is employed to ingest and bring structure to the data. Organizations can just specify the structure that they need the data in, and DS Integrate will generate code for the creation of the knowledge base in any of the formats compatible with modern cloud data such as Spark, DataBricks, Talend, Matillion, etc. Data Engineers can now upload the unstructured or structured data in a wide range of source configurations or formats including ODBC, JDBC, PDF, image, or text. DS Integrate will then convert the input into a structured data catalog and follow all coding standards and best practices to infuse it into the new data platform.
Once the knowledge base is available in the new system, DataSwitch extracts meaningful and required information using DS Democratize - an intuitive, conversational AI-driven 'Data-as-a-Service' toolkit. A business executive just has to request information from a chatbot, and it will be presented to them.
"The moment a question is asked, DS Democratize will generate a code, or equivalent SQL query, fire it onto the knowledge base and present the data in the needed format," explains Karthik. This code will be generated in whichever technology that the enterprise prefers, making the platform polyglot and data scientist friendly.
Let’s look into a recent case-study to elaborate. DataSwitch developed an enterprise-level solution with DS Integrate and DS Democratize to automate the procurement process of supplier spend management for a biotech major. Earlier, the business teams within the enterprise were facing difficulty in optimizing their tail spend analysis, management, and supplier negotiation, since the process was highly manual, that too with thousands of suppliers every month. This resulted in errors, inaccuracy, and ineffective supplier negotiations leading to higher spend in the order of millions of dollars.
The data to negotiate with these suppliers were spread across multiple supplier quotes as PDFs and images, making it tedious to analyze the entire process manually. DS Integrate enabled a seamless automated conversion of this unstructured data to a structured format. And, DS Democratize helped decipher the entire information 100x faster than the manual process. The automation and its analytics reports helped the business save tens of million dollars within a span of few months.
Global enterprises are seeking data governance while migrating all or parts of their data to the cloud. Effective data governance will ensure that your data is consistent, trustworthy, and does not get misused. ALTR, a no-code cloud-native platform for data-driven enterprises, provides robust data governance and data security as-a-service. ALTR understands data consumption and mitigates the risk of storing and sharing data.
With ALTR as an integrated partner service, DataSwitch is a trusted end-to-end platform that automates and accelerates the entire data transformation process. The platform is currently available to enterprises, and it is anticipated to be at the disposal of the data engineering community very soon.