Data warehouse optimization and modernization (DWO and DWM) are implementation strategies in which your data warehouse runs only the workloads that are best served by it. For example, data and analytics that require the fastest interactive responses should reside in a data warehouse. In contrast, massive historical data sets are ideally handled by other platforms.
Many organizations try to put all analytical workloads into their data warehouse, but this is problematic for two main reasons. First, data warehouses are expensive, and other technology options are better suited for workloads that don’t require the fastest levels of responsiveness. Second, data warehouses were not designed for many of the modern data types available today and require excessive IT time and effort to prepare these data types for analysis.
Basic DWO/DWM strategies only address the use cases below:
MapR and Arcadia Data can deliver even more opportunities for optimization, modernization, and analytical insights.
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A joint MapR and Arcadia Data deployment helps you make smarter decisions and offload the right workloads from your data warehouse. Examples include:
Interactive Analytics for End Users. MapR and Arcadia Data cost-effectively provide fast, interactive, BI-style analytics suited for most end user requirements.
Visualizations on Machine Learning Outputs. MapR is an ideal platform for machine learning frameworks, and Arcadia Data helps to make sense of all the outputs via visualizations.
Analytics on Enriched Data Sets. Add external data sets such as location-based intelligence to more easily uncover hidden insights. Use Arcadia Data visualizations (including mapping technologies) to get deeper insights from your enriched data.
Internet of Things (IoT) and Log File Data Analysis. Unstructured data types grow rapidly and can only be efficiently stored in a MapR cluster that handles the large volume and fast growth.
A sound DWO/DWM strategy entails optimal data tiering across systems, including within your platform. With MapR Policy-Based Data Tiering, you get an automated tiering approach that conveniently balances performance, cost, and capacity tradeoffs by storing, managing, and analyzing data in different data tiers: hot, warm, and cold.
Customers should begin their journey with MapR Professional Services to help define their modernization strategy and ensure workloads are operating on the right platform. DWO starts with identifying the workloads to move to MapR and Arcadia Data. From there, the deployment can grow to add newer data sources that give you more business-critical insights.
MapR Technologies, provider of the industry’s leading data platform for AI and analytics, addresses the data complexities of high-scale and mission-critical distributed processing from the cloud to the edge, IoT analytics, and container persistence. Global 2000 enterprises trust the MapR Data Platform to help them solve their most complex AI and analytics challenges.
About Arcadia Data
Arcadia Data provides the first visual analytics and BI platform native to big data that delivers the scale, performance, and agility business users need for both real-time and historical insights. Its flagship product, Arcadia Enterprise, was built from inception for big data platforms in the cloud and/or on-premises, and streamlines the self-service analytics process with search-based BI and visualization recommendations. To learn more, visit www.arcadiadata.com.