Getting Started with Big Data for Business Managers

Fastest Time to New Insights

© 2014 Datameer, Inc. All rights reserved.

How to Get Started on Hadoopfor Business Managers"

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Tony Baer @Ovum Principal Analyst Tony Baer leads Ovum’s Big Data research area. Over his 25 years in the industry, he has studied issues of data integration, software and data architecture, middleware, and application development. Having tracked the emergence of BI and data warehousing back in the 1990s, Baer sees similar parallels emerging in the world of Big Data today. His coverage focuses on how Big Data must become a first-class citizen in the data center, IT organization, and the business.

@TonyBaer

About Our Speaker"

Azita Martin @datameer CMO Azita Martin is Chief Marketing Officer at Datameer with extensive marketing leadership experience at high-growth start-ups and category-creating public companies like Salesforce and Siebel. Azita has global responsibility for scaling all aspects of Datameer’s product and corporate marketing, including defining go-to-market strategy, driving thought leadership, and increasing brand awareness and customer acquisition. Prior to Datameer, Azita built and led marketing teams for both fast-growing start-ups and major public companies, including Get Satisfaction, Moxie Software, LiveOps, Salesforce, Siebel and SGI.

#datameer @datameer

About Our Speaker"

www.ovum.com

© Copyright Ovum 2014. All rights reserved.

How to get started on Hadoopfor Business Managers"

Tony Baer, Principal Analyst

[email protected]

7 © Copyright Ovum 2014. All rights reserved.

Agenda"

§  Why Big Data & Hadoop?

§  Making the business case §  When to use Hadoop

§  How to make it happen?

§  What’s the End Game


Making the business case"

§  Address documented business challenges

§  Choose high-impact problem & solution that delivers actionable results

§  Determine whether the solution absolutely requires Big Data

This is not a data science exercise!


New data sources

Schema on read

New analytic approaches beyond SQL

Inexpensive compute cycles

•  Structured data

•  Text •  Social

networks •  Mobile data •  Machine data •  Rich media

•  Let the data drive you to the problem or insight

•  Path analytics •  Cluster

analytics •  Graph

analytics •  Streaming

analytics

•  Move compute loads from DW to Hadoop

When to use Hadoop"


New perspectives to addressing

existing problems

New data generates new revenue streams

Use case – general themes"


Agenda"

§ Why Big Data & Hadoop?

§ How to make it happen? §  Making Big Data & Hadoop first class citizens

§  Getting the right people §  Walk before you run

§ What’s the end game?


No separate Big Data silos!

“Big Data cannot exist on its own island”

Big data must become a 1st class citizen in the enterprise"

•  IT: Map to existing staff & skills

•  Data Center: Map to existing policies & rules

•  The Business: Map to existing business challenges


Get the right people"

Technical Analytics team

Business

Java/Python Developers

Data Architect

DBA

Mgmt. champion Evangelist

Domain/subject matter experts

Business owner/sponsor

Data steward/ Data curator

Some will play dual roles

Statistical experts (Supplemented by applications or tools)

Platform Specialists/ Cluster architect


Do you really need a data scientist?"

§  Creative, investigative mind

§  Statistical programming skills

§  Domain/industry awareness

§  A “nose” for data sets

§  Some database skills/awareness

§  Ability to communicate & evangelize

Applications & tools may embed data science!

Look for a team, not a rock star!


Getting there with the army you have"

§  Hadoop platform training is critical

§  Big Data analytics training is critical

§  Greater variety of data

§  Different analytics methods (beyond traditional SQL)

§  Cloud §  Reduces technology skills

requirements, depending on type of cloud service

§  Different architecture than on premises cluster deployments

§  Requires retraining if cloud used for jumpstart to on-premises


Walk before you run"

Low Road

High Road

Higher Road

Clickstream/log analytics

DW optimization

Customer optimization

Risk Management

Anti-fraud

Operational Efficiency

Create new business services

Business transformation

Big Data on Hadoop use cases


Agenda"

§  Why Big Data & Hadoop?

§  How to make it happen?

§  What’s the end game?


Set realistic goals"

•  “Hard” ROI numbers from •  DW optimization

•  Operational efficiency

•  “Soft numbers” from •  Benefits that are directly

attributable to using Big Data analytics

•  New business opportunities from Big Data

•  New capabilities for sensing & responding

Challenges are similar to any analytics project


Embrace & Extend"

IT organization

Data Center

Enterprise

Embrace Extend

Existing SQL, Java, other language skills

Mgmt for bigger, more variable data sets & use new analytic methods beyond SQL

Existing data stewardship, resource mgmt, security, perf mgmt practices

Practices to support different workload characteristics & active archiving

Existing competitive problems

Problem solving by using new data types & analytic methods to boost understanding

How to make Hadoop & Big Data 1st class citizens


Summary: The elements for getting started with Hadoop"

1. Problem

2. People

3. Training

4. Technol.

5. Document results

•  Start simple •  Choose high-impact problem & solution that delivers actionable

results •  Determine whether the solution absolutely requires Big Data

•  Extend DW teams with greater roles for developers, statistical analysts •  Don’t expect to find a “data scientist.” •  Management champion is critical

•  Get data center practitioners up to speed with Hadoop platform •  Develop understanding of how to work with new data types +

analytics methods beyond traditional SQL

•  Start small. •  If cloud used for jumpstart, architectural migration will be required for

moving on premises

•  Unless used for operational efficiency or DW optimization, benefits will rely on “soft numbers”

•  Identify business benefits that are directly attributable to using Big Data analytics

Big Data Use Cases"

The State of Big Data Market"

Working with 200+ Customers"

Social Media

Mobile Ads

Web Logs

CRM

Product Logs Transaction

Call Center

Are keywords related to customer segments?

Which campaign combinations accelerate conversion?

Which product features drive adoption?

Which features do users struggle with?

What behavior signals churn?

Are these car parts failing faster than others with different usage?

Where do hack attempts originate?

How do we determine which cell towers to upgrade?

Can we predict production failure?

Combining More Data for New Insights"


30% Lower Customer Acquisition Costs

Decrease Customer Acquisition Cost

Connected Home

Energy Consumption

Data

Reduced False Alarms

User Behavior

Improved Customer Experience

Internet of Things"


Product Catalog

CRM

Server Logs

Predictive Maintenance New Revenue Stream

New Data-Driven Service

@Datameer www.datameer.com

For the webinar:http://bit.ly/1DcEdeu"

Getting Started with Big Data for Business Managers

Data & Analytics

Transcript of Getting Started with Big Data for Business Managers