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Seamless data flow for successful digital transformation

Enterprises are in a continuous progression to transform their products, services and processes for meeting ever-changing customer needs and strategic goals. Enterprise Data Management allows businesses achieve their data-to-value goals. The transformational initiatives necessitate changes in IT landscape such as modernizing legacy applications, consolidating redundant applications, progressing to Cloud, information delivery to customers through varied new channels, etc.

The changing application landscape becomes operationally effective only when the data foundation layer is in sync with evolving applications. This could be ensured by solutions that enable digital transformation of data in an agile and cost-effective manner, from one platform to another, facilitating businesses to deliver an enhanced user experience.

The key challenges for enterprises to undergo application transformation are: 

  • Considerable time and efforts spent in data extraction, data assessment, data quality check, data transformation and data reconciliation
  • Minimal collaboration between business and IT teams during transformation
  • Poor or limited visibility into the digital transformation process

With Hexaware’s Data Modernization platform, an integrated data management solution that is built to ensure flawless execution of digital transformation initiatives, enterprises can now effectively realize their data-to-value & data2digital™ goals to deliver truly seamless & superior end-user experiences.

Why Hexaware?

We hedge the risks associated with digital transformation initiatives 

Enterprises who have made their first move towards digital transformation of data and applications landscape are looking for a solution that could hedge the risk of these projects  over-exceeding estimated budgets and timelines. Data modernization tools and IPs automate digital transformation process right from data extraction to data transformation and reconciliation.

We accelerate your Data Warehouse (DW) development

Be it developing your DW from scratch for transactional data or extending the capability of your current DW, leverage our Data Modernization toolset for accelerating these processes. Experience agility across the entire development cycle including data profiling, data quality validation, ETL code generation and reconciliation. 

We automate your data operations end-to-end

Increasing complexity of collected data poses a serious and tough challenge in front of data stewards when it comes to data operations. Multiple manual touchpoints in this cumbersome process hits business as IT teams are not able to maintain data hygiene and data synchronization. With Data Modernization platform, experience over 50% automation in data collection, data assessment and data preparation.

Key Benefits

  • ML based Data profiling
  • 10+ pre-built data masking functions
  • 1000+ configurable data quality rules
  • Advanced Data Transformation features
  • 60+ Reports and Dashboards for tracking and reconciliation
  • Reduction in manual efforts by 40% – 60%
  • Comprehensive Technology Expertise (Guidewire, AMOS, Sequel, Success Factors)

Our Data Modernization Platform

  • Data Segmentation and Movement (DASEM) allows sub-setting of data from an application database for any of the predefined data segmentation (slicing) conditions. It also offers standard masking types required by businesses and supports customization of masking rules to secure the data while copying from production to non-production environments. 

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  • This feature allows automated data profiling. The tool output helps in identifying business rules and data quality rules for data transformation process, in early stages of the project execution. It supports data science style data profiling based on R and provides insights through Data Profiler dashboards and various reports accelerating the data analysis time. ML techniques are applied to identify data outliers during the discovery phase. 

    Data Profiler helps in data modelling exercises by providing insights on most likely fact measures and dimension attributes through various reports.

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  • This feature is a user-friendly data quality rule engine that allows users to employ pre-defined rules from pre-built rule repositories as well as to create / modify business validation rules for checking data quality, based on results from the Data Profiler. Data quality dashboards and reports help users analyze data quality issues either through a top-down or bottom-up approach. The auto-correct facility helps in resolving data quality issues through the Tensai for AIOps feature.

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  • Tensai for AIOps is the ETL code generator for SSIS and Informatica. It takes various inputs from the business user such as source table / file formats, target table / file formats and transformation rules using web interface to generate the ETL code that can be imported in SSIS or Informatica. It also integrates with HexaRule to leverage data quality features for generating automated technical design documents. It offers metadata search feature to expedite the analysis for any change in data model during the development phase.

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  • This feature offers reconciliation for selective data elements from source and target to ensure that the data transformation process is executed successfully, with no data loss. It supports various mathematical and string functions during the comparison process and offers data lineage in either direction (source to target or target to source) for easy traceability of data elements available in the transformation program.

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