Driving the Digital Enterprise with Big Data€¦ · SAMPLE CASE STUDIES •Customer: A consortium...

ShareInsights

Driving the Digital Enterprise with Big Data

Mukund Deshpande – GM, ShareInsights

Confidential. Copyright © 2017 Accelerite. All rights reserved.

Big Data Market & Positioning1

What are the Key Challenges ?2

What is ShareInsights ?3

Demo4

AGENDA

© 2016 Accelerite. All Rights Reserved. Confidential. Copyright © 2017 Accelerite. All rights reserved.

Enterprise

Data Stacks

ENTERPRISE DATA STACKS


Technology: Massively Parallel Processing (MPP) Database

Workload: Decision Support1995 -

Data Stack 2.0

Technology: Hadoop –Distributed Storage & Flexible Compute

Workload: Advanced & Diverse Analytics2007 -

Data Stack 3.0

Technology: Relational Databases

Workload: Online Transaction Processing (OLTP)

Architecture Evolution:• Single Tier• Client-Server• Three-tier• Web Application

Data Stack 1.0

1980 -

DATA STACK 3.0: WHAT IS BIG DATA?


Data First, Schema Later

Schema/Structure

Data

Technology: Hadoop –Distributed Storage & Flexible Compute

Workload: Advanced & Diverse Analytics2007

Data Stack 3.0

Commodity H/W & N/WDesigned for Distributed

DATA STACK 3.0: WHAT IS BIG DATA GOOD AT ?


Analyze both Structured and Unstructured Rapid Analytics Building

Multi Structured Data: Data Stack 3.0 helps you analyze huge amounts of unstructured data

Variety of Formats: Data Stack 3.0 enables you to derive insights hidden within disparate data spread across systems and formats

Data Stack 3.0

2007

Handling LargeVolumes of Data


Fraud Detection

Security/Risk Analytics

Internet of Things

Pricing Analytics

Customer 360

KEY USE CASES FOR BIG DATA

Source: OREILLY, The Big Data Market by Aman Naimat


Challenges in

Big Data

BIG DATA ANALYTICS IS HARD …


These are your choices…

INFORMATION FLOW IN AN ORGANIZATION


Preferred ToolsUsers in an OrgKey Questions

Can you analyze theimpact due to new XXX ?

Can you generate report that looks like YYY ?

Can you reshape the data to With this additional metrics ZZ ?

Can you please collect data from newsystems ?

PlatformDeveloper

Business Users

Data Analyst

BI Developer

ETL Developer

CHALLENGES IN BIG DATA ANALYTICS!

Multiple Technologies

• Varying abstractions

• Duplication of modelling

• Hard to manage lifecycle

Evolving Landscape

• Open source technologies die quickly and painfully

• Problem of plenty – Too many databases/tools difficult to keep in sync

• Slightly different approach towards things

Skills Gap

• Extremely hard to find qualified Big Data engineers

• Poor collaboration, makes it hard for a group to work together

• Complexity of technology – Half knowledge is more dangerous than none



Solution

WHAT IS SHAREINSIGHTS?


A tool for doing end-to-end analytics.

A single tool for doing data visualization, data processing, advanced analytics, data ingestion and storage (end-to-end).

INFORMATION FLOW IN AN ORGANIZATION


ToolsUsers in an OrgKey Questions

Can you analyze theimpact due to new XXX ?

Can you generate report that looks like YYY ?

Can you reshape the data to With this additional metrics ZZ ?

Can you please collect data from newsystems ?

PlatformDeveloper

Business Users

Data Analyst

BI Developer

ETL Developer

A single tool for data analysts.

BusinessTeam

TechnologyTeam

Hadoop InfrastructureCloud Sources

Non-Relational Sources

Data Warehouse

SQL Code

Real Time Streams

Code

VisualizationLayer

Designer: Representing End-to-End Analytics

1

Execution for End-to-End Analytics

2

WHAT IS SHAREINSIGHTS?


BusinessTeam

TechnologyTeam

Hadoop InfrastructureCloud Sources

Non-Relational Sources

Data Warehouse

SQL Code

Real Time Streams

Code

VisualizationLayer

Designer: Representing End-to-End Analytics

Execution for End-to-End Analytics

Analytics Representation

Language

Code Generation Engine

Library of Tasks, Widgets & Connectors

1 2 3


SHAREINSIGHTS: UNDER THE HOOD

Rapid Analytics Development

Managed Lifecycle

Diversity of Analytics

Future Proofing

KEY VALUE PROPOSITIONS

SAMPLE CASE STUDIES

• Customer: A consortium of media, cable and technology providers.

• What: Analyze audience behavior with the help of predictive algorithms and proprietary datasets.

• Why: Quick Turnaround: & Lack of Skills

• Pricing: Subscription

Audience Analytics:

• Customer: Provider compliance and research services to providers.

• What: Do compliance reporting for providers and provide additional analytics based on the data collected..

• Why ShareInsights: Lack of Skills

• Pricing: Enterprise

Healthcare Provider Analytics

• Customer: Media Company

• What: Analyze a launch of media event and take corrective action.

• Why: Variety of Analytics & lack of skills

• Pricing: Enterprise

Campaign Analytics


Demo


Thanks!

HYBRID BIG DATA ARCHITECTURE

Hadoop Infrastructure

Cloud Sources

Non-Relational

Sources

Real Time Streams

Data

Warehouse

Visualization

Layer

Business

Team

Infrastructure

TeamTechnology

Team

Enterprise Sources

SQL Code

Code

CODE GENERATION APPROACH

IML

File1 2 43

Data

Processing

Data

Storage

Middle

Layer

Reporting

1. Hadoop: PIG

2. Hadoop: Spark

3. Spark Streaming

4. JavaScript

1.Hadoop

2. RDMBS

3. Sqlite

4. AWS S3

1.Web Service

2.ODBC

3. JDBC

ShareInsights

Compiler

1.JavaScript Engine

2.Jasper Reports

(Metadata, Consumption, Environment)

Drag & Drop UI Tool for

IML Construction

© 2016 Accelerite. All Rights Reserved.26

1. Language & SDK: The building blocks

Lan

guag

eLi

bra

ry

& S

DK

Connector SDK

• Support for CDC & Real-time

• Library of 25+ Connectors

Task SDK

• SDK in Python, R & Java.

• Easily wrap existing Lib

• Library of 100s of Tasks.

Widget SDK

• Mature SDK in JavaScript

• Library of over 70 widgets.

1) Entities:

2) Collections

3) Single Config.

1. Data 2. Task 3. Widget

4. Flows: {Tasks}5.Layout:

{Widgets}

Data ModelUnified

Security

Managed

LifecycleCentral

Deployment

3. Environment

API Driven

Collaborate & Share

On-premise & Cloud

Zero DeveloperFootprint

Unified Securityacross Layers

Manage the Lifecycle

Driving the Digital Enterprise with Big Data€¦ · SAMPLE CASE STUDIES •Customer: A consortium...

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Transcript of Driving the Digital Enterprise with Big Data€¦ · SAMPLE CASE STUDIES •Customer: A consortium...