Big Data and BI Best Practices
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Transcript of Big Data and BI Best Practices
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Big Data and BIBest Practices
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| Last Year
Yellowfin CEO, Glen Rabie
VP Sales & Services in APAC, Actian Corporation, Jason Leonidas
Your presenters
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| Last Year
Yellowfin CEO, Glen Rabie
General Manager, Actian Vectorwise, Fred Gallagher
Your presenters
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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
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Data is the new oil
David McCandlesData Journalist
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The rise and rise of Big Data
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There has always been Big Data…
Its just that now we can actually capture and mine it effectively.
Canadian Tar Fields
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Not all Big Data is created Equal
Planet Google and friends are the outliers
.
The NormLarge Telco
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Do you have a Big Data problem?
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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
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Who is benefitting from Big Data?
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Who is benefitting from Big Data?
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Why bother with Big Data?
of organizations collect more data than they can effectively use (MIT Sloan Management Review)
60%
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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%
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Why bother with Big Data?
of organizations that actively leverage Big Data say they can now make better decisions (Avanade)
84%
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Best Practices in Big Data
Jason Leonidas, Actian Corporation
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Best Practices in Big Data
Fred Gallagher, Actian Corporation
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What is Big Data?
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Best Practice #1
Focus on what you want to achieve
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It’s all about driving value
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Big Data Levers
1. Personalization2. Social3. Search4. Find opportunities5. Actionable Insights
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Best Practice #2
Identify the data you havevs
The data you need
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Does your data match what you want to achieve?
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What data do you need?
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Best Practice #3
Use the right Big Data tool for the job
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Big Data and Hadoop
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Big Data Eco-system
BIG DATA
OperationalDatabase
NewSQL“as-a-service”
NoSQLDocumentBigTable
Key ValueGraph
Social Media
Storage
Search
Hadoop AnalyticDatabases
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Best Practice #4
Use a fast database
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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.”
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User Expectations
Web-Based Business IntelligenceUsers expect results in less than 10 seconds
Mobile BIUsers expect results in less
than 3 seconds
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Use a fast database
Traditional Database Analytical Database Clustered Database
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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
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Best Practice #5
Plan for a mixed architecture
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Hadoop and BI architecture
Hadoop
Fast Database BI Tool
Transactional
External
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Best Practice #6
Ensure mass distribution of your data
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Big Data for Everyone
Visualizations
Alerts
Access Anywhere
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Best Practice #7
Tailor data delivery to each audience
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Give your audience what they want
Demographics Statistics
KPIs Collaboration
Interactive Reports
Maps
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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
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Big Data Visualization Tips
• More data requires more focus
• Interactivity is essential
• Select the right metrics
• Provide context
• Support and prompt action
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Demonstration
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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
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ConclusionQuestions
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| Last Year
@YellowfinBI
@ActianCorp
More Information
Yellowfin www.yellowfinbi.com
Vectorwisewww.actian.com/products/vectorwise
Feedback & [email protected] Yellowfin LinkedIn User Group
Vectorwise LinkedIn User Group