ACCELERATING ANALYTICS
THROUGH DATA PREPARATION
Dan Potter, CMO, Datawatch
Michele Goetz, Principal Analyst, Forrester
© 2015 Forrester Research, Inc. Reproduction Prohibited 3
Business stakeholders want to be in
command of their dynamic ecosystems
© 2015 Forrester Research, Inc. Reproduction Prohibited 4
Your business has lost its patience
— it needs data now
© 2015 Forrester Research, Inc. Reproduction Prohibited 5
Base: 1200 and *595 global data and analytics business decision-makers
Source: Business Technographics® Global Data & Analytics Survey, 2015 and 2014
Satisfaction is on the decline even as
investment in analytics is on the rise.
Q.A1: What is your level of satisfaction with analytics in your company?
53%
33%
14%
2014*
42%
36%
21%
2015
© 2015 Forrester Research, Inc. Reproduction Prohibited 6
14% Make Customer Insights an integral
part of planning
67% 59% 56%
Can’t Access Can’t Integrate Slow Updates
Source: Forrester’s Q2 2014 Intelligent Enterprise Self-Assessment Scorecard
Source: Forrester’s Q2 2014 Intelligent Enterprise Self-Assessment Scorecard
© 2015 Forrester Research, Inc. Reproduction Prohibited 7
IT just takes too long…
9%
11%
11%
12%
13%
25%
19%
23%
23%
23%
23%
25%
61%
53%
56%
53%
52%
43%
Implementing and supporting new BI and advanced
analytics technologies
Sourcing new non-customer data sets & making
them available for self-service analytics or data
science
Creating new data stores and views of structured
data for reporting and interactive query
Adding new data feeds for embedded BI/analytics
within CRM, marketing, or loyalty solutions
Sourcing new customer data sets and making them
available for self-service analytics or data science
Generating new data reports from existing data
Within days Within weeks Within months or longer
Q.A9: In general, when business users are looking for help with analytics, how quickly does
IT turn around the following requests?
Base: 3005 global data and analytics decision-makers. “Never” and “don’t know” not shown.
Source: Business Technographics® Global Data & Analytics Survey, 2015
© 2015 Forrester Research, Inc. Reproduction Prohibited 8
Business access to data is more than
just a nuisance…
› Can circumvent security when they use rogue data and
technology.
› Consume a lot of valuable time “munging” data prior to
analysis.
› Make bad business decisions because of data quality
issues.
› Can generate data silos that produce inconsistent
insights
© 2015 Forrester Research, Inc. Reproduction Prohibited 9
Strategically Surrender To Data Self-
Service with Data Preparation
© 2015 Forrester Research, Inc. Reproduction Prohibited 10
Source: Brief: Data Preparation Tools Accelerate Analytics February 2015
.
Data Preparation Tools
Software that eases the burden of
sourcing, shaping, cleansing, and
sharing diverse and messy data sets
to accelerate data’s usefulness for
analytics
© 2015 Forrester Research, Inc. Reproduction Prohibited 11
Source: Business Technographics® Global Data & Analytics Survey, 2015
Organizations are getting ready for data
self-service
67% 59%
Envision business
user flexibility to pull
and use data
Will expand or
implement data
preparation capabilities
in next 12 months
© 2015 Forrester Research, Inc. Reproduction Prohibited
Data Quality
Personal Data
Applications - Trusted
Shared Data
Internal sources – Casual Trust
Available Data
3rd Party sources – Acquired Trust
Opportunistic Data
Potential sources – Unclear Trust
In-memory DB,
Data
Warehouse,
NoSQL,
Hadoop
Governance Policies and Data
Certification
ETL/ELT,
Data
Virtualization,
APIs
External Sources
Our Data Optics Have To Change
Get beyond the
12% of data you
use
© 2015 Forrester Research, Inc. Reproduction Prohibited 13
Analyst: I want self-service…I know
good data when I see it.
› Instant self-service access to data
sources
› Reduce data wrangling time
› Collaborate and iterate on data set
preparation
› Transparency into iterative data set
design
› Transparency into data quality conditions
› Immediately visualize data with easy
push to analytics
© 2015 Forrester Research, Inc. Reproduction Prohibited 14
Data Steward: I want to drive data value
and promote data best practices.
› Can “see” data policies for production data sets
› Can measure data quality levels
› Transparency into business trusted data
sources
› Transparency into potential new data value and
policy scenarios
› Low impact deployment of data policies into
analyst preparation
› Visibility and meaning into compliance with data
policies
› Data profiling and prototype environment for
new data services
© 2015 Forrester Research, Inc. Reproduction Prohibited 15
Data Architect: I want to enable the
business with better insight
› Can “see” data requirements for
production data sets
› Collaborate with analysts speed up data
access
› Reduce/optimize resources covering ad-
hoc data support
› Create prototype data models and
databases to “test” new capabilities
› Gain visibility into data source use for
security and utilization
© 2015 Forrester Research, Inc. Reproduction Prohibited 16
Source: Data Quality Marketing Overview Q2 2015
Data Preparation is a critical piece of the
data quality governance program
Data Preparation
Self-service application to blend,
standardize, cleanse, merge data
Data Quality Tools
Data management tool
to cleanse, enrich,
standardize, match,
and merge data
Master Data
Management
Data management too to
define and orchestrate master
data models
Metadata Management
Data management tool to store and maintain data
dictionaries and data mappings for data integration
Data Ingestion
Data aggregation tools for Hadoop and NoSQL
environments that transform, match, and merge data
Data
Stewardship
Planning,
collaboration,
workflow and
reporting environment
to enable and capture
data governance
business processes
Business Glossary
Application to collect and share data descriptions
and definitions
Reference Data
Management
Define and enforce data
standards and hierarchies
Semantic
Data Maps
Intelligent graphs
that evolve by
data use to
classify and link
data
© 2015 Forrester Research, Inc. Reproduction Prohibited 17
Where data preparation sits in your
architecture
© 2015 Forrester Research, Inc. Reproduction Prohibited 18
Adopts the 4 Principles of Data Prep...
› It’s a data pipeline: Considering all data roles and
objectives to turn data into insight
› Data is personal: Enable analysts to explore and
play in the data to “know it when they see it.”
› Capture tribal knowledge quietly: Data
wrangling activity is a window into data policies
› Data prep is for all data pros: Data architects and
data stewards have a tool to prototype and test data
DATAWATCH SOLUTION FOR
SELF-SERVICE DATA PREPARATION
Dan Potter, Chief Marketing Officer
Datawatch self-service data
preparation provides
better and faster
decisions
Better
ONLY 12%
Of enterprise data is used for
information and to make
decisions. ‘Dark Data’ growing
800% Reports, web pages, JSON, log files…
Databases, Salesforce, Hadoop, etc
Faster
80% WASTED TIME
Analysts spend vast majority of
time preparing data, not
analyzing data.
Work directly with data, no scripting
Automate, reuse & deliver
• The fastest and easiest way to acquire and
prepare the widest variety of data
• Built upon the most powerful engine used by the
world’s largest organizations for 20+ years
• Runs on your laptop or server for deployments
of any scale
Introducing Datawatch Monarch
HealthCare
Government
93 of the Fortune 100 Rely on Datawatch
Financial
Services
Other
Industries
Retail
19
Demo
Question and Answer
Free Monarch Personal Edition
available for immediate download
at www.datawatch.com
Datawatch self-service data
preparation provides
better and faster
decisions
ACCELERATING ANALYTICS
THROUGH DATA PREPARATION
Dan Potter, CMO, Datawatch
Michele Goetz, Principal Analyst, Forrester
Any data including
multi-structured
Proven scalability
to thousands of
users
Remove risk of
non-managed
data & processes
Intelligent UI
with powerful
engine
DISCOVER
Datawatch Managed Analytics Platform
GOVERN
ACQUIRE
PREPARE
AUTOMATE
Automation
Service
Visualization
Engine
Content
Repository A
P
I
Governance and Control
Connectivity
Data
Preparation
Thank you
forrester.com
Michele Goetz, Principal Analyst
@FORR_Mgoetz
mgoetz@forrester.com

Forrester’s View on Accelerating Analytics and Insights with Data Prep

  • 1.
    ACCELERATING ANALYTICS THROUGH DATAPREPARATION Dan Potter, CMO, Datawatch Michele Goetz, Principal Analyst, Forrester
  • 3.
    © 2015 ForresterResearch, Inc. Reproduction Prohibited 3 Business stakeholders want to be in command of their dynamic ecosystems
  • 4.
    © 2015 ForresterResearch, Inc. Reproduction Prohibited 4 Your business has lost its patience — it needs data now
  • 5.
    © 2015 ForresterResearch, Inc. Reproduction Prohibited 5 Base: 1200 and *595 global data and analytics business decision-makers Source: Business Technographics® Global Data & Analytics Survey, 2015 and 2014 Satisfaction is on the decline even as investment in analytics is on the rise. Q.A1: What is your level of satisfaction with analytics in your company? 53% 33% 14% 2014* 42% 36% 21% 2015
  • 6.
    © 2015 ForresterResearch, Inc. Reproduction Prohibited 6 14% Make Customer Insights an integral part of planning 67% 59% 56% Can’t Access Can’t Integrate Slow Updates Source: Forrester’s Q2 2014 Intelligent Enterprise Self-Assessment Scorecard Source: Forrester’s Q2 2014 Intelligent Enterprise Self-Assessment Scorecard
  • 7.
    © 2015 ForresterResearch, Inc. Reproduction Prohibited 7 IT just takes too long… 9% 11% 11% 12% 13% 25% 19% 23% 23% 23% 23% 25% 61% 53% 56% 53% 52% 43% Implementing and supporting new BI and advanced analytics technologies Sourcing new non-customer data sets & making them available for self-service analytics or data science Creating new data stores and views of structured data for reporting and interactive query Adding new data feeds for embedded BI/analytics within CRM, marketing, or loyalty solutions Sourcing new customer data sets and making them available for self-service analytics or data science Generating new data reports from existing data Within days Within weeks Within months or longer Q.A9: In general, when business users are looking for help with analytics, how quickly does IT turn around the following requests? Base: 3005 global data and analytics decision-makers. “Never” and “don’t know” not shown. Source: Business Technographics® Global Data & Analytics Survey, 2015
  • 8.
    © 2015 ForresterResearch, Inc. Reproduction Prohibited 8 Business access to data is more than just a nuisance… › Can circumvent security when they use rogue data and technology. › Consume a lot of valuable time “munging” data prior to analysis. › Make bad business decisions because of data quality issues. › Can generate data silos that produce inconsistent insights
  • 9.
    © 2015 ForresterResearch, Inc. Reproduction Prohibited 9 Strategically Surrender To Data Self- Service with Data Preparation
  • 10.
    © 2015 ForresterResearch, Inc. Reproduction Prohibited 10 Source: Brief: Data Preparation Tools Accelerate Analytics February 2015 . Data Preparation Tools Software that eases the burden of sourcing, shaping, cleansing, and sharing diverse and messy data sets to accelerate data’s usefulness for analytics
  • 11.
    © 2015 ForresterResearch, Inc. Reproduction Prohibited 11 Source: Business Technographics® Global Data & Analytics Survey, 2015 Organizations are getting ready for data self-service 67% 59% Envision business user flexibility to pull and use data Will expand or implement data preparation capabilities in next 12 months
  • 12.
    © 2015 ForresterResearch, Inc. Reproduction Prohibited Data Quality Personal Data Applications - Trusted Shared Data Internal sources – Casual Trust Available Data 3rd Party sources – Acquired Trust Opportunistic Data Potential sources – Unclear Trust In-memory DB, Data Warehouse, NoSQL, Hadoop Governance Policies and Data Certification ETL/ELT, Data Virtualization, APIs External Sources Our Data Optics Have To Change Get beyond the 12% of data you use
  • 13.
    © 2015 ForresterResearch, Inc. Reproduction Prohibited 13 Analyst: I want self-service…I know good data when I see it. › Instant self-service access to data sources › Reduce data wrangling time › Collaborate and iterate on data set preparation › Transparency into iterative data set design › Transparency into data quality conditions › Immediately visualize data with easy push to analytics
  • 14.
    © 2015 ForresterResearch, Inc. Reproduction Prohibited 14 Data Steward: I want to drive data value and promote data best practices. › Can “see” data policies for production data sets › Can measure data quality levels › Transparency into business trusted data sources › Transparency into potential new data value and policy scenarios › Low impact deployment of data policies into analyst preparation › Visibility and meaning into compliance with data policies › Data profiling and prototype environment for new data services
  • 15.
    © 2015 ForresterResearch, Inc. Reproduction Prohibited 15 Data Architect: I want to enable the business with better insight › Can “see” data requirements for production data sets › Collaborate with analysts speed up data access › Reduce/optimize resources covering ad- hoc data support › Create prototype data models and databases to “test” new capabilities › Gain visibility into data source use for security and utilization
  • 16.
    © 2015 ForresterResearch, Inc. Reproduction Prohibited 16 Source: Data Quality Marketing Overview Q2 2015 Data Preparation is a critical piece of the data quality governance program Data Preparation Self-service application to blend, standardize, cleanse, merge data Data Quality Tools Data management tool to cleanse, enrich, standardize, match, and merge data Master Data Management Data management too to define and orchestrate master data models Metadata Management Data management tool to store and maintain data dictionaries and data mappings for data integration Data Ingestion Data aggregation tools for Hadoop and NoSQL environments that transform, match, and merge data Data Stewardship Planning, collaboration, workflow and reporting environment to enable and capture data governance business processes Business Glossary Application to collect and share data descriptions and definitions Reference Data Management Define and enforce data standards and hierarchies Semantic Data Maps Intelligent graphs that evolve by data use to classify and link data
  • 17.
    © 2015 ForresterResearch, Inc. Reproduction Prohibited 17 Where data preparation sits in your architecture
  • 18.
    © 2015 ForresterResearch, Inc. Reproduction Prohibited 18 Adopts the 4 Principles of Data Prep... › It’s a data pipeline: Considering all data roles and objectives to turn data into insight › Data is personal: Enable analysts to explore and play in the data to “know it when they see it.” › Capture tribal knowledge quietly: Data wrangling activity is a window into data policies › Data prep is for all data pros: Data architects and data stewards have a tool to prototype and test data
  • 19.
    DATAWATCH SOLUTION FOR SELF-SERVICEDATA PREPARATION Dan Potter, Chief Marketing Officer
  • 20.
    Datawatch self-service data preparationprovides better and faster decisions
  • 21.
    Better ONLY 12% Of enterprisedata is used for information and to make decisions. ‘Dark Data’ growing 800% Reports, web pages, JSON, log files… Databases, Salesforce, Hadoop, etc
  • 22.
    Faster 80% WASTED TIME Analystsspend vast majority of time preparing data, not analyzing data. Work directly with data, no scripting Automate, reuse & deliver
  • 23.
    • The fastestand easiest way to acquire and prepare the widest variety of data • Built upon the most powerful engine used by the world’s largest organizations for 20+ years • Runs on your laptop or server for deployments of any scale Introducing Datawatch Monarch
  • 24.
    HealthCare Government 93 of theFortune 100 Rely on Datawatch Financial Services Other Industries Retail 19
  • 25.
  • 26.
    Question and Answer FreeMonarch Personal Edition available for immediate download at www.datawatch.com
  • 27.
    Datawatch self-service data preparationprovides better and faster decisions
  • 28.
    ACCELERATING ANALYTICS THROUGH DATAPREPARATION Dan Potter, CMO, Datawatch Michele Goetz, Principal Analyst, Forrester
  • 29.
    Any data including multi-structured Provenscalability to thousands of users Remove risk of non-managed data & processes Intelligent UI with powerful engine DISCOVER Datawatch Managed Analytics Platform GOVERN ACQUIRE PREPARE AUTOMATE
  • 30.
  • 31.
    Thank you forrester.com Michele Goetz,Principal Analyst @FORR_Mgoetz mgoetz@forrester.com