Post on 16-Jan-2017
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
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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 advancedanalytics technologies
Sourcing new non-customer data sets & makingthem available for self-service analytics or data
science
Creating new data stores and views of structureddata for reporting and interactive query
Adding new data feeds for embedded BI/analyticswithin CRM, marketing, or loyalty solutions
Sourcing new customer data sets and making themavailable 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
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Strategically Surrender To Data Self-
Service with Data Preparation
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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 ChangeGet 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 PreparationSelf-service application to blend,
standardize, cleanse, merge data
Data Quality ToolsData management tool
to cleanse, enrich,
standardize, match,
and merge data
Master Data
ManagementData management too to
define and orchestrate master
data models
Metadata ManagementData management tool to store and maintain data
dictionaries and data mappings for data integration
Data IngestionData aggregation tools for Hadoop and NoSQL
environments that transform, match, and merge data
Data
StewardshipPlanning,
collaboration,
workflow and
reporting environment
to enable and capture
data governance
business processes
Business GlossaryApplication to collect and share data descriptions
and definitions
Reference Data
ManagementDefine and enforce data
standards and hierarchies
Semantic
Data MapsIntelligent 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
BetterONLY 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
Faster80% 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
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93 of the Fortune 100 Rely on Datawatch
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Other
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19
Question and Answer
Free Monarch Personal Edition
available for immediate download
at www.datawatch.com
ACCELERATING ANALYTICS
THROUGH DATA PREPARATION
Dan Potter, CMO, Datawatch
Michele Goetz, Principal Analyst, Forrester
Any data including
multi-structured
Proven scalability
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Remove risk of
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Intelligent UI
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Data Preparation