Establish the scope and complexity of your data universe using an inventory of all data sources. This provides a basis for decision making and demonstrates – to data stewards and executives - where the gaps and competing priorities for resources exist.
Develop a logical enterprise architecture that both business and technical team within the enterprise can understand and maintain. They can use the inventory for conversations about relationships between data domains and avoid conflicts in definitions and / or terms.
Your data inventory describes the applications and platforms where data is collected from and maintained, and reduces, the amount of effort involved in daily operations. Use the inventory to develop a strategy to integrate new Big Data sources and analytics.
Identify the data touch points for data quality monitoring and correction processes. Use information about data integration points and areas for active data stewardship intervention. Reduce inconsistencies, redundancies or gaps in data quality activities.
Understand both value and risk introduced by data, before ramping up for new Big Data sources in your organization. Address potential legal discovery issues and exposure due to regulatory initiatives, for sharing, reporting, storing / archiving data.
Establish awareness of the total amount of data collected and stored, from documenting key data life cycles, extent of data persisted in applications, data retirement practices and shelf life of the data that is considered viable, to derive the associated costs.
Conduct a thorough analysis of your existing data universe including an assessment of accountability and ownership for each data source and application, critical parts of your enterprise data strategy, responsibility for big data, handling data quality decisions. Determine current accountability gaps. Establish the mechanisms for accountability through your data stewardship and data governance activities, and shore up areas that need improvement.
With a robust enterprise data strategy for the current state of affairs now designed, you can begin to plan for introducing new big data sources to supplement analytics capabilities. Use DATAIKEN platform services and data management resources to handle volumes of data; set up the processes and data staff in place to address questions that arise with entirely new types of data. Identify and avoid areas that introduce risk.
AlphaDash provides analysts all relevant tools including a Big Data processing environment, integration with over 40 data source types, design studio, data governance policy administration, configuration and runtime controls for data governance while not limiting collaboration within teams of data analysts, data scientists, and engineers.REQUEST DEMO
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