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

Analytics & Business Intelligence (BI) Enablement

(Value Proposition)

“We help Companies orchestrate towards an improved customer experience and increased revenue”

Business Entity –A&BI2207

Company Promotional | Copyright © 2017 CloudFectiv | For General Circulation

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.



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.



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



5

Current State Data Management Deployment (Non Real-time Data Socialization & Consumption)

Leveraging Data Lakes and Enterprise Data Warehouses

External Data Business Systems

Data Lake

Operation and Metadata Store

DQAM – Data Quality and Rules Engine

Transformation Engine

Workflow Engine / Executor

Enterprise Data Warehouse (EDW)

Exploration & Adhoc Analytics

Custom Applications - Customer Behavior

Custom Applications

Business Intelligence

Tools

• Social Media • Vendors/Partners • Press (Radio, TV)

• Government • Other

• Billing • CRM • Inventory • Sales • Others



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.



7

Ultimate State Deployment (Near Real-time Data Socialization & Consumption)

Leveraging Source Systems, Data Lakes and Existing Data Warehouse


Existing Data Lake





Existing Enterprise Data Warehouse (EDW)

DQAM – Source Data Quality Assessment & Monitoring Engine

Sou

rce

s D

VL

App..Services

Data Virtualization / Abstraction Layer (Connect, Combine, Publish) - All Sources Data Services

Design tools, Optimizer, Cache, Scheduler, Monitoring, Governance, Metadata, Security

Virtualized Repositories (Current & Historical Combine) Other Virtualized Data sets/Catalogues

Data

Quality

Assessm

ent

Manager

(D

QA

M)

Co

nsu

me

rs Analytical

Reports Self-Service BI Real-Time

Dashboards Exploration

Ad-Hoc Analytics Advanced Statistical

Analysis

Custom Applications

Mobile & Social Apps

• Social Media • Vendors / Partners • Press (Radio, TV)





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.



9


Data Lake





DQAM – Source Data Quality Assessment & Monitoring Engine

Sou

rce

s D

VL

App..Services

Data Virtualization / Abstraction Layer (Connect, Combine, Publish) - All Sources Data Services

Design tools, Optimizer, Cache, Scheduler, Monitoring, Governance, Metadata, Security

Virtualized Repositories (Current & Historical Combined) Other Virtualized Data sets/Catalogues

Data

Quality

Assessm

ent

Manager

(D

QA

M)

Co

nsu

me

rs Analytical

Reports Self-Service BI Real-Time

Dashboards Exploration

Ad-Hoc Analytics Advanced Statistical

Analysis

Custom Applications

Mobile & Social Apps

• Social Media • Vendors/Partners • Press (Radio, TV)



Ultimate+ State Deployment (Near Real-time Data Socialization & Consumption)

Leveraging Source Systems and Data Lakes



10

Contact Information

http://cloudfectiv.com

Analytics & BI Enablement Practice Email: [email protected] Phone: 888-206-6120



mailto:[email protected]

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