5 th ISACA Athens Chapter Conference

Transcription

1 Rosemary M. Amato Director, Deloitte 5 th ISACA Athens Chapter Conference Big Data and Advanced Data Visualization Rosemary M. Amato ISACA International Vice President 23 November 2015

2 WELCOME INTRODUCTION Director within the Netherlands member firm of Deloitte, based in Amsterdam Program Director for Global Client Intelligence (GCI) GCI s mission is to be the one comprehensive source for timely, complete and accurate quantitative global client information Leading a virtual team which is focused on collecting data within the Deloitte network, storing the data, and delivering this information using next generation visualization capabilities to those that require it to serve clients with distinction. Previous role as Global Enterprise Risk Services (ERS) Knowledge Management leader. Focused on enabling a knowledge sharing environment for the ERS professionals throughout the world. Responsibilities included intranet as well as internet knowledge assets, managed a virtual team of knowledge advocates located throughout the world including a content editing team located in India. 12 years in the client service area of Deloitte as an experienced Risk Services Director, focused on Internal Audit, Security and Privacy, IT Audit, Business Process controls, GRC, and other Enterprise Risk Services market offerings. Speaking engagements included subjects of: CRM, KM, Social Media, Controls Transformation, GRC, Risk Intelligence, FDA/EU regulatory strategy, IT Governance and Data Visualization, Big Data, and Digital Darwinism CISA, CMA, CPA and Six Sigma Green Belt [email protected]

3 EXPECTATIONS FOR TODAY BIG DATA THE BIG BUZZ WORD How do you start tackling risk concerns that may become evident when you use Big Data? Key Concepts surrounding an understanding of Big Data will be presented Should an advanced data visualization tool be used or not used with Big Data? Qlik will be discussed with a case study of an implementation to showcase how to recognize risks within your Big Data 3

4 BIG DATA WHAT IS IT? How would YOU describe Big Data Why are companies pursuing Big Data Analytics? Are their risks in using Big Data? A big YES! - From ISACA s whitepaper on Generating Value from Big Data Analytics 4

5 BIG DATA A DEFINITION 5

6 ANALYTICS WHAT IS IT? 6

7 ANALYTICS AND DATA BIG OR SMALL 7

8 BIG DATA ANALYTICS DECISION MAKING What is the impact of making decisions based on visualization tools? Are there risks that the visualization is not accurate? Data is the basis for decision making and the amount of data available is growing. Columns of numbers are no longer sufficient we need color, shape, movement in space and time. Tools and techniques have improved and put the data into the hands of the business user the goal is to bring the analysis closer to the decision makers. 8

9 BIG DATA ANALYTICS NOT SOMETHING NEW - Florence Nightingale s visualization of Causes of Mortality in the year

10 REWARDS THINK BIGGER There are tremendous rewards to be gained, but it will require thinking (and acting) differently. 10

11 EMBEDDING ANALYTICS USING BIG DATA 11

12 VISUALIZATION A DEFINITION Visualization is a tool for making business decisions. It is primarily response to information overload. As more and more data becomes available, the amount of data is too much to visualize in a table of numbers. Visualization helps people cut down in information overload because it draws their attention to the important pieces of data. It creates the ability to see, discover and explore deeper insights within large, complex data sets 12

13 ITEMS FOR CONSIDERATION SOFTWARE CONCERNS Scalability Is the solution scalable to the quantity of data you will be searching? Computation What type of calculations, questions, discovery items will need to be computed on the fly? Cost effectiveness Have you taken into account all costs? Resilience to failure Is it sustainable? 13

14 ITEMS FOR CONSIDERATION RISK CONCERNS Do you know where the data came from? Can you audit the underlying data? Where is the data base located and secured? Can you access the data model? Is the solution maintained with proper IT controls? Are IT controls in place on the solution? 14

15 QLIK 15

16 VIDEO ON QLIK WHAT IS IT? Will link to short Video depending on attendees knowledge of this product

17 A CASE STUDY SAMPLE DASHBOARDS Flexibility in Design starting from something simple To adding more complex analyses 17

18 SAMPLE DASHBOARDS TRENDING Visualizations improve over time 18

19 DASHBOARDS ARE NOT ALL THE SAME Each has their own characteristics and purpose 19

20 RISK IDENTIFICATION STAKEHOLDERS AND THEIR EXPECTATIONS Challenges addressed during the full rollout were numerous but handling stakeholder management was critical. Identify ALL of them Determine ALL of their requirements Determine their expectations Determine their interest Determine their level of influence Plan how you communicate with them Communicate with them Manage their expectations and influence 20

21 RISK IDENTIFICATION AND DON T FORGET How do you educate stakeholders on using Qlikview? How do you contact stakeholders to start communication? Have you taken into account all costs? Is it sustainable? How do you handle change requests? What if stakeholders do not want to change? 21

22 RISK IDENTIFICATION TECHNOLOGY AND METHODOLOGY Define a roadmap The end product of an assessment should be a roadmap that details how to build out the technology, and more importantly which subject areas and dashboards should be rolled out in which order. Testing Don t underestimate testing. The dashboard should go through all testing cycles including performance testing to make sure it is ready for end users Please note all data shown today is scrambled data and does not represent any real client or real client information. 22

23 WE CHOSE QLIKVIEW WE USED THE AGILE METHODOLOGY 23

24 LESSONS LEARNED 24

25 LESSONS LEARNED Start somewhere Don t get stuck in analysis paralysis. Target having your first dashboard pilot up and running within 4 to 6 months. One size does not fit all Plan on having multiple dashboards over multiple implementation Phases. Begin with the end in mind Have a vision and a strategy for how the dashboard will progress to its end state. Information Overload What gets measured get done. Defining the right metrics requires a structured methodology. Looks are important Visual design impacts a dashboard s effectiveness. Learn and apply the basic visual design rules. Plumbing required Assess what technology is required for your dashboard and build it into your Blueprint for Success. Blueprint for Success Tie all of the lessons learned into a methodology and approach to help facilitate effective execution. 25

26 LESSONS LEARNED RELIABILITY OF THE DATA A mid-sized Oil & Gas services company implemented three versions of a dashboard that displayed both financial and operational data. The information for the dashboard came from a variety of data sources, including two ERP systems, spreadsheets, and manual inputs. All of the data was loaded by IT daily using manual processes. The dashboard received good reviews during it s initial debut, primarily because It provided visibility into a wide variety of information in one place. However, several times within the first month the load processes could not be completed so the dashboard was not available for that day. Additionally, over time the quality of the data came into question. It was a hectic job just to load the data daily, much less check it for errors. As a result of these hiccups, users began to doubt the reliability of the dashboard and used it less and less. 26

27 LESSONS LEARNED REMEMBER THE FRAMEWORK 27

28 LESSONS LEARNED WHO IS ASKING THE QUESTION??????????????????????????????? WHAT IS THE QUESTION 28

29 LESSONS LEARNED WHAT WOULD YOU LIKE TO SHOW 29

30 LESSONS LEARNED CIR IMPLEMENTATION urces.com/clientsindustri es/pages/cir-video.aspx Lync to Video Demo system sources.com/qlikview/ 30

31 CONCLUSIONS UNDERSTANDING DATA WHEN IT IS VISUALIZED MEANS CONTROLLING IT The leading institutions in industry recognize that a better understanding of data (particularly as a predictor of the future or an identifier of existing issues) can create new opportunities and makes a significant difference to managing performance, costs and risk. Every organization depends on reliable data. Managed well, it will drive revenue, reduce costs and mitigate risk. Managed poorly, it can lose customers, inflate costs and expose businesses to unbounded levels of risk. 31

32 Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited, a UK private company limited by guarantee ( DTTL ), its network of member firms, and their related entities. DTTL and each of its member firms are legally separate and independent entities. DTTL (also referred to as Deloitte Global ) does not provide services to clients. Please see for a more detailed description of DTTL and its member firms. Deloitte provides audit, tax, consulting, and financial advisory services to public and private clients spanning multiple industries. With a globally connected network of member firms in more than 150 countries and territories, Deloitte brings world-class capabilities and high-quality service to clients, delivering the insights they need to address their most complex business challenges. Deloitte s more than 200,000 professionals are committed to becoming the standard of excellence. This communication contains general information only, and none of Deloitte Touche Tohmatsu Limited, its member firms, or their related entities (collectively the Deloitte network ) is, by means of this communication, rendering professional advise or services. No entity in the Deloitte network shall be responsible for any loss whatsoever sustained by any person who relies on this communication. 32