Big Data LDN 2018: TURNING MULTIPLE DATA LAKES INTO A UNIFIED ANALYTIC DATA LAYER

Robert Eve, Senior Director
Toks Osokoya, Senior Solutions Consultant
Turning Multiple Data Lakes into
a Unified Analytic Data Layer

Digital Businesses Excel at Three Things
© Copyright 2000-2018 TIBCO Software Inc.
Optimized
Operations
Make Information the DNA
of your Organization
Compelling Customer
Experience
Own Your Destiny as a
Digital Business
Connected
Digital Products
Innovate
Intelligently

Across today’s complex data landscape, are you
getting the analytic data you need?
Data: Opportunity and Challenge
Business
Intelligence
Data
Visualization
Data Science Transactional
Apps / ESBs
Packaged
Apps
RDBMS Excel &
Flat Files
Data
Warehouse
OLAP
Cubes
Big Data
Lake(s)
XML Docs Cloud
Data
Web
Services
IoT Data

Distribution of Time Spent on Data Activities
The 80/20 rule still exists in the amount of time professionals spend
searching, preparing and protecting data vs. analytics
n = 300
Source: Data Integration and Integrity End User Survey 2017, IDC, November, 2017
How many hours per week on
average do you spend on each of the
following data related activities?

There Has to be a Better Way
“Enterprise data virtualization has become critical to every
organization in overcoming growing data challenges. These
platforms deliver faster access to connected data and support self-
service and agile data-access.” 2
“Familiar data integration patterns centered on physical data
movement (bulk/batch data movement, for example) alone are
no longer a sufficient solution for enabling a digital business.” 1
“Through 2020, 50% of enterprises will implement some form of
data virtualization as one enterprise production option for data
integration.” 1

“Data-as-a-Service”
“Data Virtualization Layer”
“Data Fabric” “Logical Data Warehouse”
“Virtual Data Lake”
“Enterprise Data Hub”
“Semantic Data Layer”
DV is a Modern Data Layer Architecture
Business
Intelligence
Data
Visualization
Data Science Transactional
Apps / ESBs
Packaged
Apps
RDBMS Excel &
Flat Files
Data
Warehouse
OLAP
Cubes
Big Data
Lake(s)
XML Docs Cloud
Data
Web
Services
IoT Data

DV Drives Data Quality, Consistency & Reuse
Application Layer
Business Layer
Source Layer
Master and
Reference
Data
Services

Data Virtualization Provides Data that is …
Governed and Secure
Agile and Flexible
Immediately Available
Business-friendly
Enterprise Grade

Data Virtualization Implementations Start
Small and Grow
Time
Enterprise-scale
Standardized Data
Services
Project
Datasets
• Architectural point of view
• Data consistency & reuse
focus
• Engineering for scale
• Project point of view
• Time-to-solution focus
• “Good enough” engineering

DV Investments Payoff Quickly
• Derive analytics and apps business value
sooner
• Add more value faster as changes occur
• More complete, up-to-the-minute, easy
to access and understand data
• Less effort needed versus ETL
• Interactive development & validation
improves quality & avoids rework
• Reuse data services on new projects
• Lower infrastructure costs, fewer
licenses, less depreciation, etc.
• Fewer support & maintenance costs
Business Value
Acceleration
Business Insight
Improvement
Development
Cost Avoidance
Data Mgmt.
Infrastructure
Cost Reduction
“By 2018,
organizations with
data virtualization
capabilities will
spend 40% less on
building and
managing data
integration processes
for connecting
distributed data
assets.”

Leaders Choose TIBCO DV
6 of Top 10
Fortune 500 Companies
3 of Top 5
Energy Companies
6 of Top 8
Pharmaceuticals
8 of Top 10
Wealth Managers
4 of Top 5
US Banks
3 of Top 5 Cable Providers
#1 US Telecom
#1 Entertainment Company

Demonstration

Big Data LDN 2018: TURNING MULTIPLE DATA LAKES INTO A UNIFIED ANALYTIC DATA LAYER

More Related Content

What's hot (19)

Similar to Big Data LDN 2018: TURNING MULTIPLE DATA LAKES INTO A UNIFIED ANALYTIC DATA LAYER (20)

More from Matt Stubbs (20)

Recently uploaded (20)

Big Data LDN 2018: TURNING MULTIPLE DATA LAKES INTO A UNIFIED ANALYTIC DATA LAYER