Prepared early 2017 as a point of view of what we're seeing emerge with Analytics, BigData, Cloud and Machine Learning.

1. Analytics Trends Report
Prepared 2017
Robert Sibo
Practice Director
Slalom Consulting
Silicon Valley

3. uses truckspulling shippingcontainers
Toingestit all,
firmsare speedilybuildingdata refineries
The cloud big data analytics arena is still evolving – far from a mature
end-state with plenty of opportunities for improvement though stacked
with great new capabilities

4. At the end of 2016 we polled our analytics leaders and vendor partners
to understand where they’re seeing investments being made
Partner/Market Risk Analytics
Master Data Management (still…)
People Analytics (Qlty of Hire, Diversity, Retention)
Analytics-driven Business Tools
Integrated Marketing Analytics / Automation
Data Services / Open Data Commercial Adoption
Machine Learning (Python, TensorFlow)
Modern Data Governance (Alation, Colibra)
Advanced Visualization & D3 Tools
Data Wrangling
Customer Personalization / ML Driven Customization
Modern Data Arch. (Spanner, Time Series DB, NoSQL)
Cloud BI Platforms (AWS, Google, Azure)Cloud BI Platforms (AWS, Google, Azure)
Modern Data Arch. (Spanner, Time Series DB, NoSQL)
Customer Personalization / ML Driven Customization
Data Wrangling
Advanced Visualization & D3 Tools
Modern Data Governance (Alation, Colibra)
Machine Learning (Python, TensorFlow)
Data Services / Open Data Commercial Adoption
Integrated Marketing Analytics / Automation
Analytics-driven Business Tools
People Analytics (Qlty of Hire, Diversity, Retention)
Master Data Management (still…)
Partner/Market Risk Analytics

5. Ubiquitous
Data
Access
Modern
Data
Governance
Contextually
Relevant
Insights

6. Our project observations and the general industry points towards the
following trends we’ll see emerge and grow in 2017+
Advanced visualization applications “moving traditional BI to modern BI”
‘Little AI’ works its way into Business Applications
Modern Data Architecture (MDA) & the Cloud
Modern data governance & metadata mastery
3rd party commercial & open data sets
”Citizen Integrators” enabled by IT

7. Advanced Visualization Business Applications
“Moving Traditional BI to Modern BI” plus a push to embed visualizations directly into business
applications is driving custom development and innovation in reporting platforms.
• Visualization tools like Tableau will continue to spread across the business moving certain
use cases off of “traditional BI”
• More advanced use cases are including custom web development to frame visualizations
along with integrated business applications and ML driven advisory services like NLP and
recommendation engine
• Collaboration and interaction is a must and many tools are moving quickly to allow this
natively in their tools (e.g. Domo)
‘Little AI’ works its way into business applications
Commercially available tools with built in machine learning capabilities will enable product
managers to embed micro customization or smart workflows processing in nearly all industries.
• Little AI is used to personalize customer and employee experience and provide smarter
workflows for everything ranging from CRM to online grocery shopping to meeting room
booking chatbots
• Machine learning techniques are leveraged in many customer/partner facing tools with
ease thanks to tools like Alteryx, Google Cloud, PowerBI making it available without the
PhD studies
Software company, Logi Analytics, polled 500 users in 2016 and
found that 60% of end users leverage embedded analytics on a
regular basis. Compare that to only 21% user adoption of standalone
self-service analytics
40%
Increase in regular usage
from embedding analytics
HubSpot Global AI Survey, Q4 2016. n=1426 consumers
74% people used
voice search in past month
47% would buy
from a chatbot

8. Modern Data Architecture & the Cloud
Cloud platforms provide big data and much more with little of the maintenance headaches. Quick to
explore and quick to add on features coming from innovators like Google.
• Quick expansion into the cloud for everything from infrastructure to analytics services
(e.g. ML API) allows companies to leap frog without large investments internally on skills
and costly implementations
• Google Spanner – Global ACID compliant database platform on the cloud provides a
unique and powerful option for global low-latency use cases
• Cloud providers move towards value-add services to increase solution stickiness including
ML APIs and data ingestion tools
• SaaS offerings provide way to bypass upgrade dilemmas by always keeping your services
up to date in exchange for a subscription fee
Modern Data Governance & Metadata Mastery
Moving beyond power point processes and definitions modern tools automatically rationalize data
sources, look at usage patterns and map data lineage from A to Z.
• Master Data Management, Data Governance and related topics haven’t gone away but
now tools are popping up (e.g. Alation and Colibra) that facilitate workflows, ownership
and monitoring of these capabilities
• Alation and others allow BI teams to monitor and automatically catalog what reports, data
sets and users are out there including SQL queries
• Real data lineage and impact analysis is coming to fruition with cataloging tools from
Informatica and Alation fulfilling a very old promise from DG tools
30-50%
YoY growth for Cloud providers
like Azure, AWS and GCP
In 2014, cloud data warehousing
services led the information
management category in
increased adoption rate, jumping
from 24% to 34% according to
surveys by Information Week
43%
Organizations looking to deploy
cloud based solutions for Big
Data Analytics in 2016 *
61%
Organizations reported
correlating data from difference
silos as one of the key challenges
for Big data *
* WebProNews Survey

9. 3rd Party Commercial & Open Data Sets
Every company is a data business and the access to it provides competitive advantages so it’s
no surprise data brokers are providing data to companies of all sorts who are mature enough
to leverage it.
• Anonymized 3rd party data sets used to provide benchmarks/baseline context for internal
reporting and even wrapped and delivered to customers as enhanced services
• Integrated commercial data sets and Open Data sets make their way into analytics tools
like Alteryx, Google Cloud Platform to make it easy to include without negotiating data
licenses or vetting for trustworthiness.
• More and more companies are providing their data to other companies as they see the
value of it outside their own business
”Citizen Integrators” enabled by IT
Business users need to build their own integration to gather and prepare data for their
self service reporting needs. Library and subscription hubs will provide democratization
of internal and external data for them.
• Data libraries (e.g. Paxata, Alteryx Gallery, Informatica Data Hub) provide users portal for
ad-hoc and subscribed access to their company’s data assets - providing the costly data
integration services behind the scenes
• Alteryx and others continue to spread across business units to fill gap of data prep tools
not filled by traditional IT run integration capabilities
• Mature ETL tools and reporting platforms are expanding quickly into this area though
By 2018 Gartner predicts 50% of integration
will be implemented by Citizen Integrators in
the business
50%
of integration will come
from Citizen Integrators
Average hours spent by business user spends collecting
data. Data scientists spend 60% of their time on
cleaning and organizing data. Collecting data sets
comes second at 19% of their time
Hours
Per Week3.6
The average marketing team is spending about 16 hours
per week on routine tasks. About 3.55 hours are spent
simply collecting and organizing data.

10. Our project observations and the general industry points towards the
following trends we’ll see emerge and grow in 2017+
Advanced visualization business applications “moving
traditional BI to modern BI”
• Visualization tools like Tableau will continue to spread across the
business moving certain use cases off of “traditional BI”
• More advanced use cases are including custom web development to
frame visualizations along with integrated business applications and ML
driven advisory services like NLP and recommendation engine
• Collaboration and interaction is a must and many tools are moving
quickly to allow this natively in their tools (e.g. Domo)
‘Little AI’ works its way into business applications
• Little AI is used to personalize customer and employee experience and
provide smarter workflows for everything ranging from CRM to online
grocery shopping to meeting room booking chatbots
• Machine learning techniques are leveraged in many customer/partner
facing tools with ease thanks to tools like Alteryx, Google Cloud,
PowerBI making it available without the PhD studies
Modern Data Architecture (MDA) & the Cloud
• Quick expansion into the cloud for everything from infrastructure to
analytics services (e.g. ML API) allows companies to leap frog without
large investments internally on skills and costly implementations
• Google Spanner – Global ACID compliant database platform on the
cloud provides a unique and powerful option for global low-latency use
cases
• Cloud providers move towards value-add services to increase solution
stickiness including ML APIs and data ingestion tools
• SaaS offerings provide way to bypass upgrade dilemmas by always
keeping your services up to date in exchange for a subscription fee
Modern data governance & metadata mastery
• Master Data Management, Data Governance and related topics haven’t
gone away but now tools are popping up (e.g. Alation and Colibra) that
facilitate workflows, ownership and monitoring of these capabilities
• Alation and others allow BI teams to monitor and automatically catalog
what reports, data sets and users are out there including SQL queries
• Real data lineage and impact analysis is coming to fruition with
cataloging tools from Informatica and Alation fulfilling a very old
promise from DG tools
3rd party commercial & open data sets
• Anonymized 3rd party data sets used to provide benchmarks/baseline
context for internal reporting and even wrapped and delivered to
customers as enhanced services
• Integrated commercial data sets and Open Data sets make their way
into analytics tools like Alteryx, Google Cloud Platform to make it easy
to include without negotiating data licenses or vetting for
trustworthiness.
• More and more companies are providing their data to other companies
as they see the value of it outside their own business
”Citizen Integrators” enabled by IT
• Data libraries (e.g. Paxata, Alteryx Gallery, Informatica Data Hub)
provide users portal for ad-hoc and subscribed access to their
company’s data assets - providing the costly data integration services
behind the scenes
• Alteryx and others continue to spread across business units to fill gap of
data prep tools not filled by traditional IT run integration capabilities
• Mature ETL tools and reporting platforms are expanding quickly into this
area though

11. Putting on a business lens we see big opportunities in partner and
customer facing areas especially
Sales & Marketing Analytics
• Supplier Responsibility rules driven by social and regulatory
pressures continues to make news for companies like Apple and
requires extensive transparency reporting and full supply chain
data management
• Fines for trading with black listed companies can be huge
financially but also take a toll on the brand
Supply Chain Analytics
• Business strategy aligned metrics and risk tolerance levels by key risks
categories (Capital, Credit, Market, Operation, Liquidity, Reputational,
Strategic)
• Regulations continue to drive innovation. The EU General Data
Protection Regulation's (GDPR) 72-hour data breach notification
requirement is set to take effect in May 2018.
• Fraud protection pushes for real-time alerting and data management
around customer and partner data where fines can be dramatic (e.g.
AML / KYC and channel partner management)
Finance Analytics
• Tools will make it easier to combine click stream and other
customer channel data with revenue, workforce and sales data
for richer insights
• Channel partner analytics allows detailed performance and fraud
monitoring and even recommend remediation such as training
and certification programs to improve channel sales
• CEOs are looking to reduce cost and increase revenue per FTE
which requires truly treating employees as assets by standing up
a People Analytics function within the organization
• Quality of Hire leveraging mixture of personality, skills and
performance modeling to optimize successful placement
• Employee Journey is common place borrowing successes seen in
marketing by mapping out the makes/breaks of sales journeys
• Tools like Visier and custom built analytic solutions are popping
up all over to address emerging demands:
• For example, $m are lost due to improper or poorly timed On/Off
Boarding that could be saved
People / HR Analytics

12. Slalom’s State of Analytics Medium Forum: https://medium.com/state-of-analytics
CIO.com’s Predictions: http://www.cio.com/article/3166060/analytics/15-data-and-analytics-trends-that-will-dominate-2017.html
Supplier Responsibility @ Apple: https://www.macrumors.com/2017/03/27/apples-2017-supplier-responsibility-report/
People Analytics Pulse Survey by PWC: http://www.pwc.com/us/en/hr-management/publications/trends-workforce-people-analytics.html
EU GDPR News: https://www.bna.com/eu-72hour-breach-n73014447213/
HBR – ‘7 Ways to Introduce AI into Your Organization’: https://hbr.org/2016/10/7-ways-to-introduce-ai-into-your-organization
Citizen Integrator - Gartner “Predicts 2015: Digital Business and Internet of Things Add Formidable Integration Challenges”, Benoit J. Lheureux et al., November 2014, Foundational May 2016
HubSpot Global AI Survey, Q4 2016: https://research.hubspot.com/reports/artificial-intelligence-is-here
Big Data Trends in Finance from MapR: https://mapr.com/blog/top-10-big-data-trends-2017-financial-services/
Tableau BI Trends 2017: https://www.tableau.com/learn/whitepapers/top-10-business-intelligence-trends-2017, https://www.tableau.com/about/blog/2016/12/whats-big-big-data-10-trends-2017-63627
Datapine Software Trends for 2017: http://www.datapine.com/blog/business-intelligence-trends-2017/#
Forrester Report: https://www.forrester.com/report/Its+Time+To+Upgrade+Business+Intelligence+To+Systems+Of+Insight/-/E-RES122481
Nucleus Research / Logi Analytics ‘State of Embedded Analytics’ Report: http://go.logianalytics.com/rs/793-ECD-841/images/2017%20State%20of%20Embedded%20Analytics_Logi_final.pdf
Gil Press @ Forbes: https://www.forbes.com/sites/gilpress/2016/03/23/data-preparation-most-time-consuming-least-enjoyable-data-science-task-survey-says/#7f2e614c6f63
DEJ’s summary and analysis of 19 vendor briefings conducted around the 2016 Strata Conference, NYC: https://www.slideshare.net/dej_io/2016-strata-conference-new-york-vendor-briefings?qid=adf2cc4e-c513-
4497-a25f-fb6c542c2edc&v=&b=&from_search=6
WebProNews Survey on Marketing Tasks: http://www.webpronews.com/survey-looks-at-time-spent-by-marketers-on-email-data-collection-2016-01/
Reading Material