Data Mashups for Analytics

Data Mashups for AnalyticsBringing Everything Together for Actionable Insights

Ben HopkinsSr. Product Marketing Manager, Pentaho

© 2015, Pentaho. All rights reserved. pentaho.com. Worldwide +1 (866) 660-75552

We Enable the Modern Data-driven Business

Modern, Cohesive Business Analytics and Data Integration Platform• Full spectrum of analytics for all key roles• Embeddable, cloud-ready analytics• Broadest and deepest big data integration

Innovation Through an Open Heritage• Open, pluggable, purpose-built for the future• Sustained leadership in big data ecosystem

Business Momentum• Over 1,500 commercial customers• Over 10,000 production deployments


Agenda

① Background

② Approaches to Data Blending

③ The Role of Data Integration

④ Real World Examples & Success


Background

Much of the value from big data will come from“mashing up” proprietary data with external and open data.

McKinsey Global Institute10 IT-enabled Business Trends for the Decade Ahead, 2013


Poll Results from pentaho.com






Background

Proportion Utilizing Unstructured Data From:

Social Media: 66%Internet of Things: 65%Mobile Device Data: 58%

“When individual sources include automated and/or manual inputs, originate from disparate systems with different architectures, and are subject to different levels of governance, an effective integration process is essential.”

From “Delivering Governed Data For Analytics At Scale,” Forrester Consulting, 2015

The most powerful insights come from blending data on demand

and at the source


On Demand and At the Source

Architected & Trusted Approach

• Designed with full knowledge of underlying systems and constraints

• Utilize most efficient point of processing

• Provide fast access, avoid unnecessary staging

• Maintains governance rules

• Preserve semantics, auditability


Where Does Data Integration Add Value?

Business Intelligence and Data Warehousing

“Effective decisions depend on aggregated, calculated, and time-series data values in a DW – data and data structure that wouldn’t exist without data integration”

Builds New and Valuable Data Sets

“Similar to a value-adding process in manufacturing, DI collects raw material (data from sources systems) and assembles it into a product (new data sets)”

360-Degree Views of Business Entities

“Success in sales and service often depends on complete views of each customer, which are typically assembled with data integration tools and techniques”

From “Ten Ways Data Integration Provides Business Value,” Philip Russom, TDWI, 2011


Data Readiness Checklist

Do I Need Data Integration Capabilities?

1. Do I need to blend several different data sources?2. Is my data cleansed and modeled?3. Do I want to enrich my data with new data sources?4. Have I already captured all the data I need?5. Will my data sources change in 6, 12, or 18 months?6. Do I need ad-hoc and drill-down analytic capabilities?

All Signs Point to Data Integration

Data Blending

Examples & Success Stories


Blending Web Analytics and Support Data

Business Question: Am I supporting all of the right browsers for my web app?

Blended by region and browser

Software Product Manager

Google Analytics web visits via API

Flat file of historical product support

requests

Android visits, but we don’t support yet


Blending Machine and Production Data

Business Question: What facility temperature is optimal for manufacturing output?

HVAC sensor data in Hadoop accessed

via Hive

Production quotas and actuals from data warehouse

Blended by facility and

time

Operations Manager

Cold temperature ranges associated with higher production across almost all facilities

See detailed mashup videos:pentaho.com/blend-of-the-week


CaterpillarDelivering a 360-Degree View of Equipment

Business Challenge• Identify opportunities for maintenance

and fuel savings in industrial equipment operations

• Predict equipment breakdowns to avoid downtime

• Extend fleet-level insights to equipment operators


CaterpillarDelivering a 360-Degree View of Equipment

Pentaho Benefits• Blend sensor data with customer data

and more into unified analytics service• Operationalize predictive ‘useful life’

models in the data workflow• Provide a revenue-generating offering

to customers that drives substantial fuel and maintenance savings


Entity 360Marine Asset Intelligence

Business User (COO) Reporting on

Operations and Efficiency

End UsersDashboards and

Reports on Machine Performance

Business Analytics Server

Data Marts

Data ScientistData Mining and Predictive Data

Governance

Local Machine and Server

Data

Fleet Data via Satellite

Cross Department

Operations Data

Data Integration

Data Integration


British TelecomProtecting Against Cyber Threats

Business Challenge• Launch new service to market: BT

Assure Cyber, an enterprise solution for cyber security insights across many data types

• Previously BT Assure Cyber could only integrate relational data sources and not big data sources


British TelecomProtecting Against Cyber Threats

Pentaho Benefits• Native support for Hadoop in an

enterprise environment• Ability to integrate telemetry data

from sensors, security controls and advanced detection tools

• Reduced detection time of cyber threats from weeks to seconds


In Closing

Next Steps

Explore more mashup examples: www.pentaho.com/blend-of-the-week

Take a look at Pentaho in the 2016 Gartner Business Analytics Magic Quadrant

Key Takeaways

Teams are taking “data mashups” to new heights

Blend data on demand and at the source

Data integration can maximize analytic value

Questions and Discussion

Thank You

Technology

Data Mashups for Analytics