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Storytelling with Data (Data Visualization)

www.pwc.com. Storytelling with Data (Data Visualization). June 12, 2014. Jason Josko Data Solutions, PwC.

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Storytelling with Data (Data Visualization)

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  1. www.pwc.com Storytelling with Data(Data Visualization) June 12, 2014

  2. Jason JoskoData Solutions, PwC • Over 14 years of experience helping clients transform their underlying data into actionable intelligence, focusing on large scale data analytics, visualization, reconciliation and data quality assurance. • Helps Internal Audit teams develop their analytics strategy as well as conduct targeted audit analytics. • Experience developing procurement compliance programs, dashboard reporting packages, and working capital improvement solutions. • BS in Accounting from University of Iowa • Interests and Passion: Storytelling with Data - Data Visualization

  3. PabaDMelloData Solutions, PwC • Over 6 years of experience in data analytics • Focus on Data Visualization and understanding business analytics needs of the clients • Experience in integrating information from multiple data sources a efficiently executing assignment using dynamic tools. • Involved in data cleansing, data preparation and visualization stages of a project • BS in Computer Science from University of Mumbai, India • Interest and Passion: Storytelling with Data - Data Visualization

  4. Kate RevaData Solutions, PwC • Over 4 years of industry experience in corporate accounting and data analytics • Focus on Data Analytics to facilitate External and Internal Audit engagements as well as Fraud Analytics and Data Visualization tools • Served clients in a variety of industries, including financial services, manufacturing, insurance, pharmaceuticals, consumer products and technology • BS in Accounting from DePaul University • CISA certified • Interests and Passion: Storytelling with Data - Data Visualization

  5. Today’s Discussion Data Creates Opportunities Analytics in Action Data Visualization Tool Landscape What are the benefits, characteristics and value of Data Visualization Analytics? QlikView and Tableau case study and live demonstration of analytics through data visualization What are the key players? What is the difference between them? Storytelling with Data - Data Visualization June 12, 2014

  6. Data Creates Opportunities Storytelling with Data - Data Visualization

  7. Data VisualizationWhat is it? • An exciting new way to incorporate raw information into a visual interactive medium Data Visualization is an emerging area of data analytics that combines quantitative information with technology and graphical design to tell stories, convey ideas and make decisions. • A way to dissect increased volumes of rows and columns of information to understand trends, patternsand make strategic, operational and tactical decisions • A powerful way to simplifythe ever increasing size and complexity of information Storytelling with Data - Data Visualization

  8. Data VisualizationWhy is it a hot topic? Storytelling with Data - Data Visualization

  9. Data VisualizationData to Insight Storytelling with Data - Data Visualization

  10. Data VisualizationData to Insight Storytelling with Data - Data Visualization

  11. Benefits of Data and Visual Analytics Clean Data Define Baseline • Refine • Analysis Quick Hits Soft Analytics Hard Analytics Identify Prove Scale Repeat Baseline Performance Storytelling with Data - Data Visualization Time

  12. Visualization • Dashboarding • Trending & comparisons Characteristics of analytics today Analytics; discovery and communication of meaningful patterns in data Big data; collection of large and complex data sets • Data • Financial, Operational • Structured, Unstructured, • Internal, External Accessibility and portability; available anytime, anywhere Storytelling with Data - Data Visualization

  13. Analytics in Action: TableauProduct Pricing Override Audit Storytelling with Data - Data Visualization

  14. Auditing Approach Leveraging Data Analytics Foundation: Leverage data to identify key risks to be addressed through the Audit Plan Planning: Plan and scope the audit to focus on high risk areas and newly identified risks Fieldwork: Develop risk based and value added analytics for the audit Reporting: Analyze results to quantify impact, and report findings utilizing data visualization Quality: Monitor managements responses through Dashboards 1 5 • Foundation • Quality Business Development • Planning 2 • Reporting 4 • Fieldwork 3 Storytelling with Data - Data Visualization

  15. I. Foundation: Risk Assessment Issue Analyze financial data to gain insight over declines in net revenue. Internal audit identified product pricing as a key risk area Action Analyze key financial data and adjust their audit plan to address their high risk areas. Impact Annual quarter over quarter revenue decline Storytelling with Data - Data Visualization

  16. II. Planning: Project Risk Assessment Unexpected spikes in price overrides Issue Varying gross margins across 3 retail channels Utilized data visualization software to analyze the stores by retail channel. Action Identified limited controls around product price overrides/adjustments have been identified Impact Storytelling with Data - Data Visualization

  17. II. Planning: Audit Scoping Issue Identify high risk stores affecting gross profit through the use of overrides Utilized data visualization software to analyze the total price override amounts against gross profit to identify outliers and anomalies Action Identified stores that had negative gross profits or negative overrides Discovered that products can have price overrides that result in losses Impact Negative gross profit due to price overrides Storytelling with Data - Data Visualization

  18. III. Fieldwork: Targeted Analytics Testing Override reason codes leading to negative gross profit Storytelling with Data - Data Visualization

  19. IV. Reporting: Confirm and Report Results Outlier of sales associate with potential unusual activity Sales associates entering in negative override amounts Sales associates overriding to negative gross profit Storytelling with Data - Data Visualization

  20. V. Quality: Remediation Follow Up Issue Monitor managements response to the findings of the pricing audit Utilized data visualization software to leverage the analytics and dashboards created during the assessment, scoping, and testing phases Action Ability to continuously monitor the compliance in a consistent manner with minimal manual effort Impact Storytelling with Data - Data Visualization

  21. Analytics in Action: QlikViewKPI (Key Performance Indicators) Dashboard Storytelling with Data - Data Visualization

  22. KPI (Key Performance Indicators) Dashboard Enable effective Risk- Based Internal Audit Approach Improve the cost and effectiveness of audits Uncover trends in new and unexpected areas Identify High Risk Areas Directly communicate with data Refresh Data on monthly basis Develop KPI Dashboard in QlikView KPI Dashboard to be included as part of the Risk Assessment package See the big picture while navigating the details – for fully informed decisions Enable Continuous Monitoring Storytelling with Data - Data Visualization

  23. Data Visualization Tool Landscape Storytelling with Data - Data Visualization

  24. Who are some of the key players? Source: Magic Quadrant for Business Intelligence and Analytics Platforms. February 20, 2014 http://www.gartner.com/technology/reprints.do?id=1-1QLGACN&ct=140210&st=sb Storytelling with Data - Data Visualization

  25. Easy to use for ordinary business users and developers Strengths Low cost to implement Connects to a variety of data sources Strengths Strengths Higher annual maintenance fee Cautions Lower licensing costs per user Limited data mining and analytic capabilities Governance, consistency and skill silos challenges Cautions Strengths Source: Magic Quadrant for Business Intelligence and Analytics Platforms. February 20, 2014 http://www.gartner.com/technology/reprints.do?id=1-1QLGACN&ct=140210&st=sb

  26. Highly customizable and easy to use Strengths Relatively low cost of ownership Associative search function Strengths Strengths Higher developer learning curve Cautions Mobile functionality Limited data mining and analytic capabilities Security and administering large number of users concerns Cautions Strengths Source: Magic Quadrant for Business Intelligence and Analytics Platforms. February 20, 2014 http://www.gartner.com/technology/reprints.do?id=1-1QLGACN&ct=140210&st=sb

  27. Advanced modeling and building analytical models Strengths Easy to use for end users Enterprise deployment readiness Strengths Strengths Limited formatting options Cautions Higher quality (stability, reliability and free from bugs) Limited data mining and analytic capabilities Support quality and cost of software concerns Cautions Strengths Source: Magic Quadrant for Business Intelligence and Analytics Platforms. February 20, 2014 http://www.gartner.com/technology/reprints.do?id=1-1QLGACN&ct=140210&st=sb

  28. Contact Information Jason Josko Office: (312) 298-3146 Email: jason.k.josko@us.pwc.com PabaDMello Office: (312) 298-5183 Email: prabhavi.dmello@us.pwc.com Kate Reva Office: (312) 298-4496 Email: ekaterina.v.reva@us.pwc.com

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