This document summarizes trends in enterprise analytics presented by William McKnight. It discusses the increasing importance of data and analytics for businesses. Key trends include greater use of data lakes, multi-cloud strategies, master data management, data virtualization, graph databases, stream processing, self-service analytics, and the rise of roles like Chief Data Officer. Data science and analytics skills will become more operational. Selection of big data platforms will consider factors like SQL support, data size, and workload complexity. Overall, data maturity correlates strongly with business success and organizations must continually advance to remain competitive.

1. Trends in Enterprise
Advanced Analytics
Presented by: William McKnight
President, McKnight Consulting Group
williammcknight
www.mcknightcg.com
(214) 514-1444
#AdvAnalytics

2. William McKnight
President, McKnight Consulting Group
• Frequent keynote speaker and trainer internationally
• Consulted to Pfizer, Scotiabank, Fidelity, TD Ameritrade, Teva
Pharmaceuticals, Verizon, and many other Global 1000
companies
• Hundreds of articles, blogs and white papers in publication
• Focused on delivering business value and solving business
problems utilizing proven, streamlined approaches to
information management
• Former Database Engineer, Fortune 50 Information Technology
executive and Ernst&Young Entrepreneur of Year Finalist
• Owner/consultant: 2018 and 2017 Inc. 5000 strategy &
implementation consulting firm
• 30 years of information management and DBMS experience
2

3. McKnight Consulting Group Offerings
Strategy
Training
Strategy
 Trusted Advisor
 Action Plans
 Roadmaps
 Tool Selections
 Program Management
Training
 Classes
 Workshops
Implementation
 Data/Data Warehousing/Business
Intelligence/Analytics
 Master Data Management
 Governance/Quality
 Big Data
Implementation
3

4. Why Are Trends Important?

5. “Beyond the Mountain is
another mountain.”

6. We Are in the Business of Data
 Our information is exploding
 Our business is real-time, all the time
 Our information differentiates us from our
competitors
 Our information quality impacts our clients, our
Associates, and our shareholders
 Our information is used and reused; information
usage drives data value
 Information is a key business asset

7. Data Maturity is Highly Correlated to Business
Success
Data
Maturity
Business
Success
7

8. Maturity Modeling
• Should give a sense of priority
• You Can’t Skip Levels – in any category
• Maturity Levels tend to move in harmony
• Midsize and smaller companies can +1
• All must be at Level 3 (some need to be at 4) this year
• Momentum is paramount!

9. Raise the Foundation of Your
Company
Raise the Foundation of Your
Company

10. The Money Tree Doesn’t Exist
Hitch your Architecture and Maturity Efforts to an
Application Budget
10

11. Data Professional Success Measurement
User Satisfaction
Business ROI and
growth instigated
Data Maturity
(Long-term User Sat
and Bus ROI)
Misc.

12. Top Trends in Enterprise Analytics for
2019 and Beyond

13. Data
Lake
Usage Understanding by the Builders
D
a
t
a
C
u
l
t
i
v
a
t
i
o
n
Data
Warehouse
Data
Mart
Sensible Divisions of Analytic Platforms

14. Cloud Storage overtakes HDFS
• Cloud Storage is more scalable, persistent and
available, and less expensive
• Public Cloud Providers back up Cloud Storage
and support compression, making the cost of
big data less
• HDFS has better query performance
• HDFS has storage formats Parquet & ORC that
cannot be used on Cloud Storage
• Cloud Storage object size limits and PUT size
limits
14

15. Multi-Cloud
Becomes the
Norm
• Disparate data-related
objectives difficult to
pursue with agility in a
single-cloud strategy
• Kubernetes emerging
15

16. 2019: The Year of Master Data Management
Source #1
SSN_NO X(9)
Claim_NO X(10)
Div_eff_dt X(10)
Source #2
Pol_ID 9(9)
Clm_NO X(10)
Stt_dt X(8
Source #3
Cust_ID X(10)
Claim_ID 9(9)
Beg_dt 9(8)
MDM
CLM_IDDec(15)SUB_ID Dec(13) EFF_DT DATE
MEMBER CLAIM GROUP
16

17. Data Virtualization Provides the Enterprise
Data Fabric
Consistent and timely access to right-placed
data
Data Warehouses
Marts & Cubes Operational
Data Stores Transactional
Sources
File Systems
Big Data
Enterprise Data Virtualization
17

18. 2019: The Year of the Graph
• Stores entities and relationships
• Entities are “nodes”
• Relationships are “edges”
• Nodes and edges have properties
• Queries traverse the graph
• Nodes can be homogenous or heterogenous
• Consistent execution times not dependent on number
of nodes

19. Stream Processing
• ETL is Insufficient for this combination:
– Data platforms operating at an enterprise-wide scale
– A high variety of data sources
– Real-time/streaming data
• Enter Message-Oriented Middleware aka Streaming and message queuing
technology
19
Streaming
Platform
Streaming
Platform
Change logsChange logs
Streaming data pipelinesStreaming data pipelines
Messaging or
Stream processing
Messaging or
Stream processing
Request - ResponseRequest - Response
DWDW HadoopHadoop
Streaming
Platform
Change logs
Streaming data pipelines
Messaging or
Stream processing
Request - Response
DW Hadoop

20. AI is disruptive
Data is the Foundation
Data’s New Highest Use Will Be Training AI
Algorithms

21. Data Visualization Footprint Escalates
Treemaps Background Mapping InfoGraphics
Sparklines Bullet Graphs Scatter Plots

22. Self-Service Takes Off
• Technology delivers right-curated data, i.e., with
• Metadata
• Data Quality
• Performance
• An understanding of usage
• Technology can focus on more value-added activities
– Developing new applications
– Expanding data in data warehouse and improving its quality
– Incorporating new technologies to improve performance
• Technology becomes more of a partner rather than a
roadblock to business users
– Business users more responsible for BI capabilities
– Technology more supportive of business needs

23. Chief Data Officer Goes Mainstream
• Objectives
– Manage the project portfolio
– Create accountability
– Protect the company
• Data & Analytics Business Executive
• Data Strategy
• Data Maturity
23

24. Organizations Acknowledge Chief Information
Architect/Chief Analytics Officer
• Leads the process in every organization to vet practices and
ideas that accumulate in the industry and the enterprise and
assess their applicability to the architecture
• Looks “out and ahead” at unfulfilled, and often unspoken,
information management requirements and, as importantly, at
what the vendor marketplace is offering
• A job without boundaries of budget and deadlines, yet still
grounded in the reality that ultimately these factors will be in
place
• Solves tactical issues, but does so with the strategic needs of
the organization in mind
• Ensures there is a true architecture in place and followed

25. Data Science Pioneers Lock In
• Data Science Pioneers
– Let the Data Speak
– Use of Statistical Models
– Machine Learning
– Deep Business Implications to Work
– Deal in Algorithm Management
• Some fake-it-till-you-make-it Data Scientists
make it
• First wave of Data Science leaders emerge
– And reap the exponential benefits
25

26. Data Team Dynamics
• Business departments have clearly staked a claim in building their
architectures
– Still need dedicated technology professionals to do the work
– The notion of an "IT professional" is alive and well
– The reporting structure is more complicated than ever
• Acknowledgement of the need for data deployments to be near the
business unit in organization charts
• Strategists and implementors are seeing a reduction in the challenges
posed by internal grist and resistance to change
– Dependence on certain individuals is lessened with the cloud, and
in 2019, many will declare their organization unshackled from
resistance to progress
– Acceleration of acceptance and some challenging personnel
moments inside the data apparatus in organizations
26

27. Analytics Skills Go into the Operational
Environment
Data Lake
DW
DM
DM
27

28. Operational Big Data Platform Selection
SQL
Data
Size
Workload Complexity
Key-Value
Document
Column Store
Graph
SQL

29. A New Dataset: Bio Data
29

30.  There’s more maturity
in moving imperfectly
than in merely
perfectly defining the
shortcomings
 Build credibility
 Don’t be afraid to fail
 Don’t talk yourself out
of having a new
beginning
Have an open mind
No plateaus are
comfortable for long
That resistance is not
about making
progress, it’s the
journey

31. Second Thursday of Every
Month, at 2:00 ET
Presented by: William McKnight
President, McKnight Consulting Group
www.mcknightcg.com (214) 514-1444
#AdvAnalytics