Data Lakes for Business: Big Data 2018

IT & DATA MANAGEMENT RESEARCH,
INDUSTRY ANALYSIS & CONSULTING
Data Lakes for Business:
Big Data 2018 End-User Research Results
John Myers
Managing Research Director
Enterprise Management Associates

Watch the On-Demand Webinar
Slide 2 © 2018 Enterprise Management Associates, Inc.
• Data Lakes for Business: Big Data 2018 On-Demand webinar is
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Featured Speaker
John Myers, Managing Research Director, EMA
John has nearly 20 years of experience in areas related to
business analytics and business intelligence in professional
services, sales consulting, product management, industry analysis,
and research. He helps organizations solve their analytics
problems, whether they are related to operational platforms like
customer care, billing, or applied analytical applications, such as
revenue assurance or fraud management. John established
thought leadership in emerging data management paradigms,
such as big data (combination of multi-structured and relational
data sets) applications and NoSQL access data stores.

Logistics for Today’s Webinar
An archived version of the event recording will be
available at www.enterprisemanagement.com
• Log questions in the chat panel located on the lower
left-hand corner of your screen
• Questions will be addressed during the Q&A session
of the event
QUESTIONS
EVENT RECORDING

Join the Conversation…
Submit your questions or comments to the panel
using: @JohnLMyers44 #bigData

Research Sponsor

Agenda
• Adapting to Data-Driven Organizations
• Expanding Landscape of Data
• Power of Digital Transformation
• Effectively Using Data at Scale
• Speeding Implementation
• Automating Deployments
• Lingua Franca of Business
• Data Privacy
• Cataloging and Governance
• Hybrid Data Ecosystem
• Question and Answer

Data Lakes for Business:
Adapting to Data-Driven Organizations

Progressive Strategies for New Environments

Adoption of Data-driven Strategies

Data-Driven Strategy Impact on Revenues
1Organizations adopting
data-driven strategies are
1.5x more likely to be
above $100b in revenues
.5x
72%
Organizations not adopting data-
driven strategies only about 72% as
likely to be above $1b in revenues

Multiple Workloads

2018 Big Data Research Highlights

Respondent Demographics

Panel Respondents
150Respondents from business
and technology leaders
across North America

Company Size

Industry Segments

Total Projects
572Big data implementation
projects from 150 respondents

Big Data Maturity Scoring

Activity vs. Achievement

EMA Big Data Maturity Score

Example of Maturity Score:
Industry Segment

Big Data Maturity Score Impact on Revenues
4Robust maturity
organizations are 4.1x
more likely to be above
$100b in revenues
.1x
42%
Organizations with a
Developing/Struggling maturity
score are only about 42% as likely to
be above $1b in revenues

Expanding Landscape of Data

Influx of New Data Sources

Pain of Data-Driven:
Ever Increasing Data Landscape

Multiple Platforms for Multiple Workloads
73%
of respondents indicated
between 2-6 platforms
within their data landscape

Power of Digital Transformation

Importance of Streaming to Data-Driven
Real-Time Applications
Mobile and Online Path Analysis
Streaming Device and Sensor Data

From the Firehose:
Streaming Strategy

Privacy vs. Ingestion:
Streaming Obstacles

Effectively Using Data at Scale

Flow of Data and Speed of Business

Application of Machine Learning:
Data Science Strategy

Data Science Leadership
#
All organizations
Leadership for data
science efforts are coming
from “marketing, sales,
and finance.”

Speeding Implementation

Nimble and Flexible Implementations:
Keeping Pace with Cloud

Speeding Implementation:
Cloud Strategy

Cloud Drivers
#
Robust maturity
organizations
“Improved collaboration”
between disparate groups
across the organization

Automating Deployments

Increase the Scale and Quality:
Importance of Orchestration

Improving Deployment:
Orchestration Strategy

Orchestration Benefits:
Differences in Maturity

Lingua Franca of Business

Business Stakeholders Dominate:
Project Data Consumers

Connecting Business with Big Data:
SQL as a Data Access Layer
90%
“How would you describe
the importance of SQL as
a data access layer
associated with your big
data initiative?”

Privacy: The New Boogie Man…

Data is the New Oil:
Who owns the data?

Protecting Data:
Privacy Strategy

Different Than You Might Think:
Data Privacy Standards
Top
“Personally Identifiable
Information” and “Payment
Card Information Data
Security Standard”

Cataloging and Governance

Making It ALL Possible

Building a Catalog:
Metadata and Governance Strategy

Improve Access:
Vision for Metadata and Governance Strategy
#
All levels of maturity
“Create a single point of
access for all of my
company’s shared
metadata”

Hybrid Data Ecosystem:
EMA Big Data Reference Architecture

Data-Driven Requires a Flexible Environment

Addressing the Needs of Business

Core Components of Data-Driven Business:
Heart of the Matter

Selecting Platforms to Meet Requirements:
Business Drives Requirements

Workloads to Meet Data-Driven Initiatives:
From Exploration to Machine Learning

Feeding the Data-Driven Organizations:
HDE Data Consumers

Connective Tissue to Bring It Together:
Completed HDE

Arcadia Data. Proprietary and Confidential
• Big data is/has evolved
• Business value will drive
future use
• Architectures will continue
to expand
Next Steps

Question and Answer

Join the Conversation…
Submit your questions or comments to:
@JohnLMyers44 #bigdata #hybridDataEcosystem

Question and Answer:
Please log Questions in the Q&A Panel
Get the 2018 “Data Lakes for
Business: Big Data 2018” Research at
https://www.enterprisemanagement.com/research
Available June 2018!
More Information on the EMA Hybrid Data
Ecosystem logical architecture:
http://research.enterprisemanagement.com/hybridDa
taEcosystem.html

Data Lakes for Business: Big Data 2018

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