Moving Data More Efficiently
83 percent of data migration programs fall short of expectations and go over time and budget.
- Some furniture is not needed.
- Other furniture, like couches, won’t fit.
- Areas like cabinets need to be redesigned.
- Certain amenities need to be acquired, such as electrical appliances.
- Unwanted data, requiring data cleansing.
- Redundant data that won’t add value in the new environment.
- Data needs to be transformed and enriched to fit in.
- New data discovery and aggregation structures for enhanced productivity and analytics.
Most organizations get so excited about advancing a big data initiative, moving to the cloud, or implementing some other enterprise initiative that they lose sight of the complexity of data migration.
In a traditional data migration approach, ETL jobs, APIs, or integration components are frequently utilized to transform information and move it from one system to another. Developing a data transfer fabric using these tools is effort-intensive, costly, and requires intrusive integration with source and destination systems. This reduces the speed of data migration activities and the overall experience.
A delayed or slow data migration severely reduces the competitiveness of a company. It negatively impacts its customer experience, can result in serious legal and regulatory risks, and dents the morale of its workforce.
Robotic process automation (RPA) provides a competitive advantage by playing a very tactical, low-cost, and non-intrusive role in migrating your information (data and content) from one system to another, quickly and safely.
- Fast. Where it would usually take company months to figure out the best replacement, bots can provide a fix in both the short and long terms based on the company's strategic goals and objectives.
- Affordable. Bots can be deployed in a matter of weeks, saving time and resources with an error-free IT solution.
- Scalable. Bots can be easily scaled up or down based on downtime and application complexity.
- Easily managed. Bots can be easily managed and throttled by business users via a dashboard.
RPA ensures a faster rollout, resulting in the quicker realization of your revenue and more accurate alignment to enterprise strategy, lending a competitive edge.
What Can a Bot Do?
- Duplicate Records. Based on the toolset, there is often an out-of-the-box capability to identify and filter duplicate records.
- Incomplete Data. Based on configured properties, bots can identify and remove incomplete records.
- Non-Performing Assets. In tandem with business rules and predictive capabilities, bots can identify and remove an entity that doesn’t provide value.
- Enhance Data Structure. With business rules and Cognitive capabilities, bots can identify entities and connect them to different data enrichment services or APIs to enhance the entity.
- Language Conversion. Bots can translate text between languages.
Data Discovery and Aggregation
- Information Classification. Based on the target layout, its configuration, and business requirements, bots can harness information from multiple systems, aggregate them, classify them, and inject them into a target application or data lake for analytics.
- Pattern Recognition. Bots can process large amounts of raw data into understandable patterns for institutional decision-making.
- Context Extraction. Bots can extract relevant information from a given piece of text, such as the overall sentiment, key phrases, possible encountered errors, and the language used.
With its capability to provide backend and surface automation, RPA can move information by entity or in a more granular fashion. It can move screen by screen or table by table based on business requirements, resource availability, and the rollout roadmap.
At a high level, integration capabilities provided by bots are classified as surface integration or backend integration.
- Login to web applications and fetch data by performing “search and extract” using application modules.
- Connect to mainframe applications via their terminals.
- Connect to a database browser to fetch information by executing queries.
- Invoke APIs and web services (REST, SOAP).
- Execute database queries to gather data.
- Invoke data services or stored procedures (via a wrapper).
Typically, during data migration, we take a holistic approach to analyze and structure data and content to align with the new enterprise standards. This helps generate better intelligence. When a data migration exercise is done right, many process and data improvements can be identified.
RPA, as a tactical solution, helps improve overall data governance and standards.
Senior Enterprise Application Architect
Animesh Jain heads Prolifics’ Robotic Automation and Process Innovation practice. With over 15 years of experience, he specializes in the digital business automation suite of tools. As a thought leader, has helped many clients with their digital transformation initiatives.
He is involved in all facets of project lifecycle, including assessment, estimation, end-to-end architecture and solution design, implementation, governance, performance, and maintenance of business processes and rules using the IBM suite of tools.