We identify and analyze our clients’ business requirements, recommend solutions and assist them in implementing these solutions successfully.
Strong Enterprise Information Architecture is needed for organizations to stay ahead of competition, and there is a need to continuously invest & innovate to attract buyers in the market. Effective use of data from internal and external sources plays an important role here. We offer the following strategy and consulting services to assist our clients in their new initiatives and help them envision and mature their information architecture.
To stay ahead of the competition, organizations have to use predictive analytics that inform them about what can happen in the future, based on past data. There are numerous advanced analytics techniques like Markovian methods and Bayesian algorithms. These help in combining multiple parameters and defining a model that can predict future results, based on past data. We also take into account various business functions and their interdependence; external influencing factors; geographical spread of business; and past behavior of the organization; to define the analytics roadmap.
Our Analytics Maturity Assessment helps organizations decide on preparatory steps to align with their analytics roadmap. We thoroughly review the existing information architecture landscape from a business and technical perspective, identify gaps and offer future recommendations.
While few organizations have legacy data warehouses, there are also some that have data warehouses that are a couple of years old. There could also be few others that have been considering a brand new Enterprise Information Management (EIM) architecture. We understand both Greenfield and Brownfield implementations, and work closely with business and IT teams to discover, analyze and strategize their future roadmap for new warehouse architecture. This includes Big Data management architecture, where data is semi-structured, unstructured, or structured, but unknown. Data could be in persistent, semi-persistent or non-persistent storage. Architectural principles that warrant minimum data movement, but effective information delivery would be applied in the definition of this architecture.
The success of a BI/DW (Business Intelligence/Data Warehousing) solution is deep-rooted in the technology that is selected and used. This could vary across organizations, and hence, technology evaluation becomes an important pre-requisite for any EIM initiative. We conduct technology evaluation and rationalization to select the best set of technologies that align to their warehouse strategy.
Our data architecture team leverages industry best practices and frameworks such as The Open Group Architecture Framework (TOGAF) in enterprise data architecture definition. Data modeling differs across industries and could be done either as a Third Normal Form (3NF) or as a dimensional data warehouse. We have adopted various industry-standard 3NF data models and implement them for our clients. We also leverage our proprietary industry-specific data models defined as dimensional models for implementation.
Data Integration Strategy
Data being a corporate asset, involves three key elements in its governance – people, process and technology. We work closely with business and IT teams to define a data governance policy.
Considering the quick growth rate of data warehouses and data marts, an archival policy becomes extremely important. Archival policy definition helps in retaining the right data online and archive the unused data. Curbing explosive data growth has become a challenge for organizations. If not done efficiently, business-critical data could go offline. Through robust data retention policies, inactive data can get intelligently relocated, while maintaining integrity and seamless access to information in the future.
Reporting & Visualization Strategy
We work closely with business users, act as a thought partner to define a complete set of reports & visualizations, and data dissemination through a secure BI portal; and define the roadmap to achieve them.
Power users need capabilities beyond reporting to perform Adhoc analysis. Online Analytical Processing (OLAP) models are built to allow slice and dice of data across various dimensions and look for data patterns. We empower end users to build their own analytical views by offering data mash-up capabilities and provide them self–service BI capabilities.
We define dashboards and scorecards that help enterprises view and interact with data to measure, monitor and manage business decisions, using both financial and non-financial parameters. We help organizations get an at-a-glance view of their operational, tactical and strategic information to allow them to make better business decisions.
Big Data Strategy
As the Digital era awaits us, the data we will be dealing with in the near future will source from various input systems at a high velocity and in seamless volume. Organizations have started using unstructured data to derive insights on their businesses and customers. We offer Big Data strategy, to assess the available unstructured data and its benefits, thus building a future road map to thrive and achieve maximum profits from the available big data silos.
Enterprise Performance Management Strategy We help organizations build an integrated performance management system, which forms the backbone of their management operating system and serves as a foundation for an agile enterprise. Our performance management system delivers a balance of standard, as well as flexible and customized services. This includes common definitions and calculations, common processes, and a common management information interface; as well as flexibility. This is done through multi-Generally Accepted Accounting Principles (GAAP), International Financial Reporting Standards (IFRS) compliance and management reporting, scenario planning & analysis, and alternate hierarchies (including entity and product roll-ups, workforce planning, sales planning and finance planning).
We define financial consolidation plans for multi-entity organizations, taking into account hierarchies and intercompany transactions. Data-quality issue resolution and generation of regulatory compliance reports are essential outcomes of enterprise performance management strategy.