oracle end-to-end analytics across big data and data warehouse for data monetization

End-to-End Analytics Across Big Data and Data Warehouse for Data Monetization CON3296

Satya Bhamidipati, Senior Principal, Advanced Analytics Gokula Mishra, VP, Big Data & Advanced Analytics @GokulaMishra Business Analytics Product Group October 26, 2015

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Copyright © 2015, Oracle and/or its affiliates. All rights reserved. |

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The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.

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Program Agenda

Drivers for End-to-End

Use Cases

End-to-End Analytics

Q&A

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Program Agenda with Highlight


Use Cases


Q&A

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Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |

Data-Driven Decisions #1 for execs1

Analytics key to growth, competitive advantage2

Firms that adopt DDD perform better than firms that don’t

1Gartner 2014 CEO Study, CIO Magazine Study 6

2MIT Study “Strength in Numbers”


Businesses

• 90% created in last two years • 50 billion devices by 2020 • Governance, risk and

complexity

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Copyright © 2015, Oracle and/or its affiliates. All rights reserved. | 8

Data & Analytics Creates New Value

Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 9 9

Data & Analytics Disrupts Industries

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | 10

Bigger Smarter

Easier

Cheaper Better

Faster VALUE IN ANY FORM


Speed over consistency

Visual data discovery

Embedded analytics

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Business user demands are changing

Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 12

IoT Cloud

Mobile Social

Data & Analytics

Digital Demands

End-to-End

Digital Forces Powering Growth and Innovation


Key Components of End-to-End Analytics

SELF SERVICE REPORTS QUALITY &

GOVERNANCE

DISCOVERY & VISUALIZATION

ANALYTICS AT SCALE

UNIVERSAL DATA ACCESS

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1. How and what new data sources are being created that is very important and relevant to you?

2. Are you combining data and analytics to drive new insight?

3. Are you building a data analytics platform that allows for experimentation, self-service as well as SCALE end-to-end?

4. Are your analytics aligned with user analytics maturity?

5. How will you govern data and analytics end-to-end?

Five Questions…




Use Cases


Q&A

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Creating Value with Data Combining New Data


Combat Fraud

Near real Time Data

External Data


Creating Value with Data Business Insight


• Accelerate Insights

High Performance Analytics

Customer Segmentation


Creating Value with Data Optimization


Optimize Offerings

Large Volumes

Complex Algorithms


Creating Value with Data IOT


Improve Safety

Maintenance Data

Sensor Data


Creating Value with Data Customer 360


Online Interaction

Real Time Decisions Improve Service




Use Cases


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Predictive Analytics



Data Mining Provides Better Information, Valuable Insights and Predictions

Customer Months

Cell Phone Churners vs. Loyal Customers

Insight & Prediction Segment #1 IF CUST_MO > 14 AND INCOME <

$90K, THEN Prediction = Cell Phone Churner

Confidence = 100% Support = 8/39

Segment #3 IF CUST_MO > 7 AND INCOME <

$175K, THEN Prediction = Cell Phone Churner, Confidence = 83% Support = 6/39

Source: Inspired from Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management by Michael J. A. Berry, Gordon S. Linoff

R

http://search.oraclecorp.com/search/search


Data Challenges and Analytics

• Diverse Data Types

• Extremely Large Volumes

• Complex Algorithms

• 3D Visualization

• Simulation

• Highly scalable computing power



Traditional Approach for Analysis

• Define the business challenge

• Data Preparation

– Identify

– Extract Data

– Ingest Data

• Build model

• Deploy Model

• Visualize the Results



Analytics Process


Data Analyze

Business Objective


Oracle Solution

• Data in the Database

• Added Algorithms

• Visual Interface


User tables

Oracle Database

Database Compute Engine

?x


Analytic Methods


Classification

Regression

Anomaly Detection

Attribute Importance

Association Rules

F1 F2 F3 F4

K Means Linear regression Naïve Bayes Neural Networks Support Vector Machines Singular Value Decomposition Principle Component Analysis


Analytics on Hadoop Big Data Appliance



Requires a Fundamentally New Approach

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quickly transform and enrich it to make

it better

unlock big data for anyone to discover

and share new value

A single intuitive and visual user interface, to...

find and explore big data to understand its

potential

find explore transform discover share


Analytics on Hadoop


BDD


End to End Analytics


?x

User tables

Oracle Database

Database Compute Engine

Connectors

Connectors


Oracle Advanced Analytics—Best Practices

1. Start with a Business Problem Statement

2. Don’t Move the Data

3. Assemble the “Right Data” for the Problem

4. Create New Derived Variables

5. Be Creative in Analytical Methodologies

6. Quickly Transform “Data” to “Actionable Insights”

7. Automate and Deploy Enterprise-wide

Everything is Different; Nothing is Different


Today’s Evolving Analytics Infrastructure

Data Fast Data

Events Actions

1 2 3

Streams

Data Management

Reservoir Factory Warehouse

Results

People

Data Services

Smart Things

Data Lab

Data Science Discovery Data Sets

Apps

Packaged

Custom

Business Analytics

Visualization

Reports

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• Built for cloud with enterprise class software

• Business driven self-service

• Advanced visualizations including mobile

• Fast cloud based data loading & metadata modelling

Most Complete

BI Cloud Service

BICS

BDDCS (Future)




Use Cases


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Q & A

Oracle Confidential – Internal/Restricted/Highly Restricted

Gokula Mishra @GokulaMishra gokula.mishra@oracle .com

Satya Bhamidipati [email protected].

oracle end-to-end analytics across big data and data warehouse for data monetization

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