Analytics & Business Intelligence (BI) Enablement (Value Proposition)

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Betty Gregory
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1 Analytics & Business Intelligence (BI) Enablement (Value Proposition) We help Companies orchestrate towards an improved customer experience and increased revenue

2 Narrative Companies are constantly striving to understand their customers/subscribers behavior. Understanding customers/subscribers behavior can help them harness more revenue. Given the right data, they will be able to create offerings that are more aligned with their customers/subscribers base. For example specific offerings for specific social media, video streaming or map applications etc.. Unfortunately, capturing and aggregating this information involves analyzing many external and internal data sources. How to cost effectively combine and publish these datasets in near real-time is considered by many to be a very arduous task. 2

3 Narrative The deployment of an architecture which incorporates a virtualized data abstraction layer will be a cost effective solution that will allow for them to connect, combine and publish internal & external data (Government, Private entities, Education, Web, Television, Social Media etc..) and an individual in near real-time. Based on this architecture Entertainment & Media companies marketing executives and others will be able to: a) Increase revenue by creating packages which are tailored to their subscribers/customers. b) Have information with respect to what is popular and unpopular with their subscribers/customers. c) Near real-time insights without the deployment of costs prohibitive data warehouses and other data repositories. 3

4 Narrative Currently most companies use a combination of Data Lakes, Enterprise Data Warehouses, and Other Repositories to manage and socialize data to their data consumers (marketing, executives, ) See slide 5 4

5 Current State Data Management Deployment (Non Real-time Data Socialization & Consumption) Leveraging Data Lakes and Enterprise Data Warehouses Exploration & Adhoc Analytics Custom Applications - Customer Behavior Business Intelligence Tools Custom Applications Operation and Metadata Store Data Lake DQAM Data Quality and Rules Engine Transformation Engine Workflow Engine / Executor Enterprise Data Warehouse (EDW) External Data Social Media Vendors/Partners Press (Radio, TV) Government Other Billing CRM Inventory Sales Others Business Systems 5

6 Current State Deployment (Disadvantages) Cannot easily leverage the power of enterprise data sources, internal, external, cloud, in-memory platforms, caching and messaging. Cannot easily deliver data through REST and self-service data services. Does not provide a clean user interface for both business users and developers. Changes to the sources, integration or output data services take a great deal of time to accomplish. Does not deliver on-demand real-time data access to data sources. Does not provide for data services capable of scaling horizontally and vertically to meet most analytical and application needs. 6

7 Sources DVL Data Quality Assessment Manager (DQAM) Consumers Ultimate State Deployment (Near Real-time Data Socialization & Consumption) Leveraging Source Systems, Data Lakes and Existing Data Warehouse Analytical Reports Self-Service BI Real-Time Dashboards Exploration Ad-Hoc Analytics Advanced Statistical Analysis Custom Applications Mobile & Social Apps Virtualized Repositories (Current & Historical Combine) Other Virtualized Data sets/catalogues Data Virtualization / Abstraction Layer (Connect, Combine, Publish) - All Sources Design tools, Optimizer, Cache, Scheduler, Monitoring, Governance, Metadata, Security App..Services Data Services Operation and Metadata Store Existing Data Lake DQAM Data Quality and Rules Engine Transformation Engine Workflow Engine / Executor Existing Enterprise Data Warehouse (EDW) External Data Social Media Vendors / Partners Press (Radio, TV) Government Other Billing CRM Inventory Sales Others Business Systems DQAM Source Data Quality Assessment & Monitoring Engine 7

8 Ultimate State Deployment (Advantages) Can easily leverage the power of enterprise data sources internal, external, cloud, in-memory platforms, caching and messaging. Can easily deliver data through REST and self-service data services. Provide a clean user interface for both business users and developers. Changes to the sources, integration or output data services take minutes to accomplish. Deliver on-demand real-time data access to data sources. Provide for data services capable of scaling horizontally and vertically to meet most analytical and application needs. 8

9 Sources DVL Data Quality Assessment Manager (DQAM) Consumers Ultimate + State Deployment (Near Real-time Data Socialization & Consumption) Leveraging Source Systems and Data Lakes Analytical Reports Self-Service BI Real-Time Dashboards Exploration Ad-Hoc Analytics Advanced Statistical Analysis Custom Applications Mobile & Social Apps Virtualized Repositories (Current & Historical Combined) Data Virtualization / Abstraction Layer (Connect, Combine, Publish) - All Sources Design tools, Optimizer, Cache, Scheduler, Monitoring, Governance, Metadata, Security Operation and Metadata Store Data Lake External Data DQAM Data Quality and Rules Engine Social Media Vendors/Partners Press (Radio, TV) Government Other Billing CRM Inventory Sales Others Other Virtualized Data sets/catalogues Transformation Engine Business Systems Workflow Engine / Executor DQAM Source Data Quality Assessment & Monitoring Engine App..Services Data Services 9

10 Contact Information Analytics & BI Enablement Practice Phone:

Solution Vision. Analytics and Business Intelligence (BI) Enablement

Solution Vision. Analytics and Business Intelligence (BI) Enablement http://cloudfectiv.com Analytics and Business Intelligence (BI) Enablement Solution Vision The purpose of this document is to provide information about CloudFectiv Analytics and Business Intelligence (BI)