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Analytics Information Architecture Implementation

Organizations often spend multiple years in defining their enterprise information architecture, and then develop a large multi-year program to realize it. We leverage our expertise in architecting large-scale complex BI/DW (Business Intelligence/Data Warehousing) applications and provide EIM (Enterprise Information Management) implementation services.

  • ​​Enterprise Data Architecture
    Enterprise Data Architecture is typically multi-layered and spans from heterogeneous sources of data to the information delivery layer. Varied levels of expertise are involved in architecting the different layers.

    Data Warehouses can be centralized, federated or even logical. We provide recommendations, and design various infrastructure layers of a Data Warehouse – right from underlying hardware, operating system, database and/or other storage. We define Massively Parallel Processing (MPP) architectures for excellent query throughput and design solutions using data warehouse appliances and build them as logical warehouses where Big Data is used.

    We help organizations consolidate their disparate warehouses into a single unified warehouse that reduces the total cost of ownership associated with redundant hardware, software, tools and processes. In addition to this, we help in decommissioning the old platform, and also perform data rationalization activities.

    To stay ahead in the competition, it is imperative for organizations to revisit their Enterprise Data Architecture on a periodic basis and carry out a re-architecture exercise.

  • ​Data Migration & Integration
    Through our data integration services, we enable enterprises to integrate their organizational data from disparate sources (internal and external) and achieve a single version of truth. Such data may be retained as granular or aggregated to a higher level of granularity as required by the business.

    Data could be integrated from heterogeneous data sources, including Big Data sources, and in many cases, the ETL (Extract, Transform, Load) window available to load data is limited. With streaming data, there is a need to capture and use that data in real-time. The large data volumes generated by the second make it imperative for organizations to have effective change data capture mechanisms. We handle our development to cater to all these situations. In addition, there could be complex transformations to create required business information. We perform data integration application development to handle such complexities, while also being powerful in performance.

    As organizations plan for newer systems of records to handle complex business scenarios, there is a need to migrate data from their legacy databases or other forms of storage into the new system. On some occasions, organizations may move from one platform to another or may change their data warehouse. In such scenarios, we help organizations move data from their existing environment to a new environment by efficiently managing migration planning, execution and post-migration activities.

  • ​​Data Quality & Governance
    Data Quality impacts the ROI of every data-dependent business system. The quality of data depends on design and production processes involved in generating the data. Our Data Quality services help organizations derive reliable, usable and dependable data. We perform data profiling, standardization and cleansing in order to deliver good-quality data to our clients.

    Implementing a data quality program effectively depends upon a good data governance program. We help define various metrics to monitor and measure the quality of data and to govern it as an asset of the organization. Development, execution and supervision of architecture, policies, practices and procedures are essential to address all the information needs and to efficiently manage the entire data lifecycle in an enterprise. We collect, prepare, use, maintain and retire data with robust controls and audit trails. We leverage proven processes for continuous improvement, enabling organizations to reconcile disparate views, ensuring a single version of truth within and outside the enterprise.

    Data security is an important facet of business. If data is not controlled effectively, sensitive data could fall into the wrong hands. With unsecured data, an organization’s reputation is at risk. Through our data masking services, we prepare data in a freely usable form, available for testing, development, training and research – all of these done without losing the characteristics of original data.

  • Master Data Management (MDM)
    Master Data (mostly comprising customer and product domains) is usually shared across transactional and analytical applications. Business transactions could be effective with a single version of Master Data and similarly the analysis could result in better future strategies as well. We offer MDM strategy and implementation services to help organizations address their MDM challenges through consistent and accurate master data. This enables meaningful data analysis across the enterprise. Master Data implementations could be in various styles such as consolidation, harmonization or centralization. We execute MDM implementations through an appropriate style as strategized with business.Reference data (which does not change so frequently, but is still a master) is again shared across transactional and analytical applications. Reference data could be public, such as SWIFT BIC codes in the Finance industry, ICD 9/10 codes in the Healthcare industry or ACORD codes in the Insurance industry. It could be semi-private such as D&B codes or private such as HR and Finance codes. We help in managing temporal referential integrity, cross-domain mapping and hierarchy management. Our Data Governance policy includes versioning mechanism for maintaining multiple versions of reference data.
  • ​Metadata Management
    Information could be meaningless if it is not documented properly. Different lines of businesses would have their own interpretations, resulting in chaotic meetings and businesses running on gut feelings rather than being driven by data. Our Metadata Management services help organizations set up an effective metadata repository, which is managed and maintained to provide relevant data at the right time. We cover technical, business and operational metadata, thus leaving nothing to speculation.

    Data Warehouse/Data Mart Maintenance encompasses model maintenance and health check services. A change in data model may be required while changing source data structures or while enhancing reporting functions. We provide model maintenance services at both, logical and physical model levels. We also offer various DBA (Database Administration) services and conduct regular health checks.

  • ​Big Data Analytics
    In addition to the huge amount of internal data that organizations churn out every day, they have also started looking at leveraging external data (that could be unstructured, semi-structured or with an unknown structure). In such cases, there is a need to explore and analyze data, adopt it if it suits business needs, provide analysis and direction to run the business efficiently, and retire when the data is no longer required. High speed is extremely essential while performing all of these activities as such data is susceptible to quick changes. We offer services on Big Data right from Consulting, Architecture Definition and Proof-of-Concept to Implementation and Support.

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