The practice of Data Management is essential to virtually all organizations in all industries that desire to reduce operating costs and increase revenue. Data Management methodologies and processing techniques are used extensively in virtually all aspects of today’s enterprise to satisfy organizational information and knowledge needs ranging from customer service requests to forecasting sales and production needs.
There are six primary considerations in effective data management strategies: data integrity; accessibility, backup, archive, disaster recovery and data availability. In our Data Management consulting and implementation efforts, we carefully analyze and consider each of these factors in designing the best overall solution with the lowest TOTAL cost of ownership for our clients.
In today’s business environment, an organization’s information processing needs not only continuously grow larger, but become more complex as business processes and software systems evolve. Multiple geographical locations, data sources, data formats and applications present unique challenges and contribute to the difficulty of data storage, maintenance and utilization. Data Science Automation extends enterprise data management to other organizational layers from the production floor to the boardroom.
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