big data and bi best practices slidedeck

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http://www.actian.com/ Watch Glen Rabie, CEO of Yellowfin, and Fred Gallahger, GM of Actian Vectorwise take you through 7 of the Best Practices for Big Data and BI.

TRANSCRIPT

Big Data and BIBest Practices

| Last Year

Yellowfin CEO, Glen Rabie

General Manager, Actian Vectorwise, Fred Gallagher

Your presenters

Taking Action on Big Data

- 50,000.00

100,000.00 150,000.00 200,000.00 250,000.00 300,000.00 350,000.00 400,000.00 450,000.00

Qph

H@10

0GB

Non-Vectorwise Vectorwise

History of 100GB TPC-H Performance BenchmarksComposite Queries Per Hour (Non-Clustered)

About Actian and Yellowfin

Making Business Intelligence easy

Data is the new oil

David McCandlesData Journalist

The rise and rise of Big Data

There has always been Big Data…

Its just that now we can actually capture and mine it effectively.

Canadian Tar Fields

Not all Big Data is created Equal

Planet Google and friends are the outliers

.

The NormLarge Telco

Do you have a Big Data problem?

Big Data for Everyone

AnalystConsumers

• Big data is not just for data scientists and bespoke projects

• Its for decision makers and data consumers• It needs to be anchored in the real world

Who is benefitting from Big Data?

Who is benefitting from Big Data?

Why bother with Big Data?

of organizations collect more data than they can effectively use (MIT Sloan Management Review)

60%

Why bother with Big Data?

of organizations investing in Big Data initiatives expect ROI within 1 year (Harris Interactive)

70%

of organizations see Big Data as a big business opportunity (Harris Interactive)

70%

Why bother with Big Data?

of organizations that actively leverage Big Data say they can now make better decisions (Avanade)

84%

Best Practices in Big Data

Fred Gallagher, Actian Corporation

What is Big Data?

Best Practice #1

Focus on what you want to achieve

It’s all about driving value

Big Data Levers

1. Personalization2. Social3. Search4. Find opportunities5. Actionable Insights

Best Practice #2

Identify the data you havevs

The data you need

Does your data match what you want to achieve?

What data do you need?

Best Practice #3

Use the right Big Data tool for the job

Big Data and Hadoop

Big Data Eco-system

BIG DATA

OperationalDatabase

NewSQL“as-a-service”

NoSQLDocumentBigTable

Key ValueGraph

Social Media

Storage

Search

Hadoop AnalyticDatabases

Best Practice #4

Use a fast database

Slow Query Performance is the #1 issue in BI

Gartner Magic Quadrant Data Warehousing70% of data warehouses experience performance constrained issues of various types

BI Survey 10: Why BI Projects Fail?1. Query Performance Too Slow

TDWI Best Practices Report“45% Poor Query Response the top problem that will eventually drive users to replace their current data warehouse platform.”

User Expectations

Web-Based Business IntelligenceUsers expect results in less than 10 seconds

Mobile BIUsers expect results in less

than 3 seconds

Use a fast database

Traditional Database Analytical Database Clustered Database

Consider the hidden costs

Spend Less on HardwareGet faster results on smaller hardware configurations.

Spend Less Time Database Tuning

Faster deployment and BI projects. No more aggregates,

cubes, complex schemas, etc

Best Practice #5

Plan for a mixed architecture

Hadoop and BI architecture

Hadoop

Fast Database BI Tool

Transactional

External

Best Practice #6

Ensure mass distribution of your data

Big Data for Everyone

Visualizations

Alerts

Access Anywhere

Best Practice #7

Tailor data delivery to each audience

Give your audience what they want

Demographics Statistics

KPIs Collaboration

Interactive Reports

Maps

Visualization is powerful

Looks like Pac-man Does not look like Pac-man

169 41

Looks like Pac-man

Does not look like Pac-man

Big Data Visualization Tips

• More data requires more focus

• Interactivity is essential

• Select the right metrics

• Provide context

• Support and prompt action

Demonstration

Big Data and BI Best Practices

1. Focus on what you want to achieve2. Identify the data you have vs The data you

need3. Use the right Big Data tool for the job4. Use a fast database5. Plan for a mixed architecture6. Ensure mass distribution of your data7. Tailor data delivery to each audience

ConclusionQuestions

| Last Year

@YellowfinBI

@ActianCorp

More Information

Yellowfin www.yellowfinbi.com

Vectorwisewww.actian.com/products/vectorwise

Yellowfin LinkedIn User GroupVectorwise LinkedIn User Group

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