Data Trends & Opportunities in the

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1 Data Trends & Opportunities in the AIIM Webinar Nov. 6, 2017 Managing Partner,AlyData Copyright 2017 AlyData

2 About Jay Zaidi 11 years Led data management and analytics programs at Fortune 10 Financial Services company (USD 2 Trillion portfolio). Direct report to the CDO for the last 5 years. 7 years Management consultant at various firms including PriceWaterhouseCoopers LLP, Commerce One Global Services,articles and the DOW Chemical Company. Authored two books on data-driven leadership and Authored over 90 articles on data management, analytics, and the role of the Chief Data Officer (CDO). jayzaidi@alydata.com Twitter LinkedIn : Articles : LinkedIn Pulse We b : Published two books on Amazon on Data-Driven Leadership in July, 2016 and 90 articles on data management and analytics. Copyright 2017 AlyData 2

3 Data Trends & Opportunities Age of Data Massive Disruption Opportunities and Risks The Data Value Pyramid Differences Between BI & Data Science Data Science Opportunities, Process, Landscape, Tools, Skills Data Science Resources Copyright 2017 AlyData 3

4 Organizations are experiencing data volume growth of 30% to 50% annually.

5 Massive disruption is happening in every sector - your company may be next The Common Thread Across Disruptors They are Data-driven not Technology-driven! Copyright 2017 AlyData 5

6 This is the new reality of the data ecosystems in a firm. a double-edged sword...opportunities and risks... ON PREMISE CLOUD Risks Data Quality Data Lineage Context Data Security Process Transparency Data can be used to create business value through innovation but presents risks as well Copyright 2017 AlyData 6

7 RIM practitioners and management must become data driven and evidence-based to maintain their organization s competitive advantage and be successful in the market.

8 THE ACKOFF PYRAMID (DIKW) Wisdom Knowledge INSIGHTS Information Data Organizations strive to gain KNOWLEDGE AND WISDOM from their DATA. Copyright 2017 AlyData 8

9 THE DATA VALUE PYRAMID Built on a RIM Foundation MATURITY LEVEL DATA SCIENCE (Statistics, Machine Learning, & Artificial Intelligence) BI/ANALYTICS (Descriptive, Diagnostic, Predictive, & Prescriptive) REPORTING (Transactional, Operational, Ad- Hoc, & SelfService) DATA & INFORMATION MANAGEMENT (Data Strategy, Data Governance, Data Quality, Data Platform & Architecture, & DataOperations) RIM DATA &INFORMATION (Storage, Security, Privacy, Taxonomy, &Classification) Copyright 2016 Jay Zaidi Copyright 2017 AlyData 9

10 THE DATA VALUE PYRAMID MATURITY LEVEL DATA SCIENCE BI/ANALYTICS REPORTING DATA & INFORMATION MANAGEMENT Uncover hidden patterns in data Understand complex behaviors,trends, and inferences Apply advanced algorithms and machine learning to solve complex problems What happened? Whydid it happen? What is likely to happen? What should I do about it? Static view of transactions Static view of operations On demandreports/dashboards Semantics Accountability Inventory Quality Process DATA & INFORMATION Data Models Data withcontext Copyright 2017 AlyData 10

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12 Data science, also known as datadriven science, is an interdisciplinary field about scientific methods, processes, and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining.

13 The differences between BI and Data Science... Business Intelligence Data Science Copyright 2017 AlyData 13

14 Data Science Opportunities In Every Sector RISK Treasury or Currency Risk Fraud Detection Credit-card Fraud Accounts Payable Recovery Anti-money Laundering CUSTOMER ANALYTICS Acquisition and customer behavior/segmentation Customer retention Predicting Lifetime Value Wallet Share Estimation Customer Churn Prediction Reactivation Likelihood Merchandise pricing Location of new stores Product layout in stores Merchandising Inventory Management Shrinkage Analytics RETAIL MARKETING ANALYTICS Targeting Price and promotion strategy Campaign effectiveness Customer Segmentation Cross-selling/recommendation Channel optimization. NATURAL LANGUAGE PROCESSING Document classification Information extraction Chatterbots HEALTHCARE ANALYTICS Patient diagnosis and classification Disease modeling Claims Review Prioritization Medical Fraud Prescription compliance Readmission risk Survival Analysis Organizations and companies live in a highly competitive and dynamic environment. Data and digital transformation is essential for success.

15 The Data Science Process 15

16 Data by itself is not useful. It s the Insights that matter RIM FOUNDATION DATA PREP & DATA ANALYSIS 80% EFFORT 20% EFFORT INSIGHTS

17 80% time and energy spent on preparing data for analysis. This is where RIM practitioners can add tremendous value.

18 The Data Science Landscape Copyright 2017 AlyData 18

19 Top 10 Tools Used in Data Science Copyright 2017 AlyData 19

20 Adding new skills is beneficial If you are technically inclined then some training in math and statistics and programming will be extremely valuable. If not, then you can focus on learning about data science, machine learning, and artificial intelligence and their application and building your domain knowledge, soft skills, communication, and visualization capabilities.

21 Data Scientist Pay In Singapore (2016 in Singapore $ s) Source: Copyright 2017 AlyData 21

22 A few valuable Data Science resources Articles Data Science Central Top 50 Data Science Resources KD Nuggets Free Data Science Resources For Beginners al.com m/top-data-scienceresources/ Training Udacity Coursera Khan Academy Copyright 2017 AlyData 22

23 AlyData has partnered with leading vendors to develop data management and data science solutions for clients... Converged Data Platform. Data wrangling for small and big data. Data Catalog Solutions that Connect the Right People to the Right Data Visual Analytics for Big Data. Data Governance process automation. Sensitive Data Governance. Copyright 2017 AlyData 23

24 Recap - 6 Key Takeaways 1 Companies and RIM practitioners must become data-driven or get disrupted. 2 There are tremendous opportunities for RIM Practitioners. 3 Data Science is built on a strong Records and Information Management foundation. Disruption Tremendous Career Opportunities The Data Value Pyramid 4 Data by itself is not useful. It s the Insights that matter. 5 Learning new skills (e.g., Data Science) is critical for career growth. 6 Develop a Career Plan to achieve personal goals. Copyright 2017 AlyData 24

25 Appendix Copyright 2017 AlyData 25

26 A few articles I ve authored Culture Defeats Strategy - Here Are 11 Ways To Win Successful CDOs Tell Stories Based on the Insights Derived From Data To Compete Leaders Must Liberate 85% Of Their Data Data Value Pyramid - A Framework For Investing in Data and Analytics To Generate Tangible Business Value General Data Protection Regulation (GDPR) - Companies Must Comply By May 2018 or Face Hefty Fines 6 Key Ingredients For Building a Multi-Billion Dollar Data Driven Company The 11 Data Management Knowledge Areas Copyright 2017 AlyData 26

27 There are opportunities forimprovement...context, quality, security, and process... Significant time spent finding and understandingdata 60% to 70% effort spent on data curation and preparation Data lineage is an important componentbut typically missing Cost savings of 6% to 10% and productivity gains of 30 % to 50% result by investing in automated metadata tagging of data, profiling for quality, discovering dark data, andgrc processes. Dark Data - 85% acquired data not used for anything meaningful and vulnerable Lack of Accountability of data assets and weak governance 6% to 10% IT operations budget spent on data quality Copyright 2017 AlyData 27