Big Data in the Nordics 2012

Size: px
Start display at page:

Download "Big Data in the Nordics 2012"

Transcription

1 Big Data in the Nordics 2012 A survey about increasing data volumes and Big Data analysis among private and governmental organizations in Sweden, Norway, Denmark and Finland.

2 Unexplored Big Data Potential in the Nordics Big Data has rapidly become one of the most discussed trends within the IT industry, with its common definitions of volume, velocity and variety. The benefits of being able to manage the constantly variable and exploding data volumes are vast and key analyst firms see Big Data as one of the technologies to watch and adapt to during At the same time, the term Big Data is broad and opens up for personal interpretations and definitions. Analysis can for example mean one thing for a BI expert and something completely different for an IT manager. This is the first study about how organizations in Sweden, Norway, Denmark and Finland manage increasing data volumes. The Nordic region is often regarded to be in the forefront of new technology with successful startups, high Internet penetration rates and wide use of mobile technology. The main conclusion from this survey is that there is still unexplored potential in Big Data analysis. Nordic organizations still lack the knowledge and motivation, despite the benefits of engaging in more advanced data analysis. 19% Unstructured data analysis is important The challenges with Big Data are real and they will remain. Fortunately, there are technologies and procedures available to become more responsive, competitive and profitable. The survey also shows clearly that normal reporting often is mistaken as true business analysis, probably due to available reporting tools that solve a few of the managements needs. Another main finding is that unstructured data is very under-used in the analysis. Variable data from for example support web sites, as well as other digital sources, should be analyzed as well, not only static data in the databases. Hardy Nelson Nordic Head of SAP Database & Technology 2

3 Executive Summary The importance of Big Data analysis is growing in the Nordic region But there is still an important task for the industry to educate and communicate the business benefits of unstructured and variable data analysis Nordic organizations prioritize structured data analysis Unstructured data analysis not well understood in the Nordics More than half of the companies claim to be working with real-time data analysis Data not consolidated in real-time to an Enterprise Data Warehouse, rendering enterprise wide real-time analysis impossible Difference within the Nordics when it comes to Big Data prioritization, budget allocation and management prioritization Denmark leading and Finland trailing in Big Data prioritization and deployment in the Nordics Data analysis and business intelligence is stated as an integrated part of the normal business processes Big Data analysis in the Nordics through traditional reporting vs. new Big Data specific technologies The key objective with data analysis is to create forecasts and optimize processes. But predictive analysis is only an objective for 10 percent and customer clustering only by 4 percent New investments in Big Data is also driven by cost reductions and profitability analysis Nordic organizations do not measure the effects of data analysis projects, mainly because they do not see the purpose or the need to analyze the results Analytics and data analysis is now viewed as a necessary function in most companies Finance, sales and IT departments are most often involved in the data analysis Approximately half of the respondents use external consultants for Big Data 77 percent claim that they use traditional databases for Big Data analysis Use of traditional relational databases may point to lack of real Big Data analysis Structured-only data analysis may explain the large percentage of small dataset sizes (70 percent <20TB, 52 percent <5TB) The use of specialized technology such as Hadoop and MapReduce is very rare Correlates to the small number of respondents who reported unstructured data analysis 3

4 Big Data Priorities What is the priority of increased data volumes within your organization today? Not prioritized 30% Base 445 Very prioritized 40% More than two thirds of the respondents prioritize the issue of increasing data volumes. 40 percent see it as a very prioritized issue, a clear indication that Nordic organizations are aware of the challenges. Somewhat prioritized 30% This is a question that growing and it s extremely important for us to priority It is a constant headache for us. We try to revise our Big Data routines and explore how to work with storage, etc. There are many different thoughts around this, especially for us working with IT. 4

5 Big Data Priorities What is the priority of increased data volumes within your organization today? The local differences are most visible in Denmark and Finland. The result is, however, likely due to cultural differences in priority evaluation. 100% 80% 8% 29% 50% 32% 29% 60% 30% 30% 40% 63% 30% 20% 38% 41% 20% 0% Denmark 75 Finland 88 Norway 90 Sweden 191 Not prioritized Somewhat prioritized Very prioritized 5

6 Structured vs. Unstructured Data How important is data analysis to your organization? Structured data has been the foundation for traditional business data analysis. The results from this survey confirm that production and relational data is a key priority. 100% 80% 60% 6% 18% 52% But more interesting is the results for unstructured and variable data. More than half of the respondents do not see any importance in analyzing e.g. online content, customer responses, etc. This is information becoming increasingly important for organizations that 40% 76% 29% want to quickly respond to changes in e.g. buying patterns and opinions. 20% It is therefore an important task for the industry and everyone 0% Structured % Unstructured 449 involved in business analysis, data warehousing and IT strategies to educate and communicate the business benefits of unstructured and variable data analysis. Not important Somewhat important Very important 6

7 Structured vs. Unstructured Data How important is data analysis to your organization? The results show that Danish organizations set the highest priority for unstructured data analysis. And analysis and BI experts in Finland have a challenge 100% 80% 4% 23% 2% 31% 10% 12% 6% 13% to clearly communicate the advantages to Finnish organizations. 60% 40% 73% 67% 78% 81% 20% 0% Denmark 74 Finland 90 Norway 91 Sweden 193 Not important Somewhat important Very important 7

8 Structured vs. Unstructured Data How important is unstructured data analysis (per country)? 100% 80% 60% 40% 20% 37% 24% 39% 52% 43% 57% 24% 55% 26% 0% 4% 19% 19% Denmark 75 Finland 90 Norway 91 Sweden 193 Not important Somewhat important Very important 8

9 Structured vs. Unstructured Data What are the proportions between structured and unstructured data? Do not know 100/0 90/10 80/20 70/30 60/40 50/50 40/60 30/70 20/80 10/ The results show that there is a widespread lack of knowledge about unstructured data in the Nordics. By not putting enough attention to the variable data, the organizations miss many opportunities to become more effective, competitive and profitable. Only 6 percent of the respondents claim that marketing and sales data is used as the basis for Big Data analysis decisions. That includes advertising campaigns, events and customer satisfaction surveys. 9

10 Structured vs. Unstructured Data How do you decide which unstructured data type to include in your Big Data analysis? Marketing, sales data 6% Do not know 12% Business demands or client needs 15% Base 409 Do not analyze unstructured data, have no need, have not discussed the topic 45% Management decisions, ad-hoc 21% 10

11 Current Data Analysis What type of data do you analyze today or plan to analyze? Production data 31% Pictures Customer and market surveys News articles 9% 7% On-line forums 4% Social media (blogs etc.) 8% Content on internal web sites 11% Web logs 14% 24% When responding on detailed questions about the type of data being analyzed today, it is clear that the Nordic organizations have a need for improvements. Only 24 percent include customer and market surveys in their analysis, which is very low depending on the valuable results such activities generate. Only 4 percent include variable content on online forums. Production and relational data in traditional databases dominate. Internal documents 11% 22% Relational data 84% Other 32%

12 Involvement Is Big Data discussed within your management? It is a task for any management to ensure that business decisions are based on as much information and useful data as possible. This survey shows clearly that Nordic managers Do not know 8% Base 449 still have more to do. The organizations are talking about Big Data analysis (38 percent of the managers). But the discussions are mostly focused on cost and technology issues not how the Yes 38% No 54% results can be used. If yes, what is discussed? 39% General strategic issues 32% Data management and storage, data volumes, new solutions and systems 15% Optimized processes, cost control and increased customer benefits 11% User availability, security, reports and analysis 3% Business Intelligence 12

13 Involvement Is Big Data discussed within your management? 120% The local differences are most visible in Denmark and Finland. The results could again likely be related to cultural differences. 100% 9% 12% 7% 7% 80% 60% 40% 37% 65% 56% 55% 20% 0% 54% 22% 37% 39% Denmark 76 Finland 89 Norway 91 Sweden 192 Do not know No Yes 13

14 Involvement Is data analysis and Business Intelligence (BI) part of your usual business processes? Do not know 1% No 15% Base 448 Yes 84% Traditional data analysis and business intelligence (BI) are seen as part of the normal business processes in the Nordics (84 percent). And there are no major differences between responses from the four countries. However, the responses clearly indicate that the organizations are working with basic analysis and reporting not Big Data analysis and business intelligence. It s included in our core processes, so in that sense it s part of our business processes. Yes, but we are a bit behind, that are things being done about it. 14

15 Involvement Is data analysis and Business Intelligence (BI) part of your usual business processes (per country) 100% 80% 60% 40% 20% 4% 16% 80% 15% 85% 1% 21% 78% 1% 11% 88% Traditional data analysis and business intelligence (BI) are seen as part of the normal business processes in the Nordics (84 percent). And there are no major differences between responses from the four countries. However, the responses clearly indicate that the organizations are working with basic analysis and reporting not Big Data analysis and business intelligence. 0% Denmark 76 Finland 88 Norway 90 Sweden 193 Do not know No Yes 15

16 Involvement What departments and functions regularly participate in data analysis? Base 446 Finance, IT, sales and marketing are mostly involved internal data analysis projects a result that confirms the picture from other markets. Embedded into business processes Human resources 11% 24% Production 27% Research & Development Marketing 14% 35% Sales 41% Finance 57% IT 45% Other 32%

17 Budgets for Big Data Is Big Data analysis part of your budget work? Do not know 7% Base 448 Approximately half of the Nordic organizations include Big Data analysis in their budgets. There are signs of change (51 percent) but not a clear prioritization. Yes 38% No 54% We try to include that in our budgets since it soon will be a major topic to manage. Not the term itself but we continuously improve our systems. 17

18 Budgets for Big Data Is Big Data analysis part of your budget work (per country) 100% 80% 60% 3% 32% 13% 65% 1% 43% 8% 45% 40% 20% 65% 56% 47% 21% 0% Denmark 75 Finland 89 Norway 91 Sweden 193 Do not know No Yes 18

19 for Big Data Analysis What are your main objectives to invest in Big Data analysis? Identifying long term trends 20% Sentiment analysis (specific for finance/trading) Control over enterprise data Profitability analysis Compliance Risk mitigation Cost reductions 7% 15% 24% 21% 40% 37% The given reasons for working with Big Data analysis is another indication that Nordic organizations are focusing more on traditional reporting than true analysis. The available data could be used to a lot more. The analysis is most often financially and sales related. 40 percent want to perform profitability analysis and 37 percent prepare for cost reductions. 15 percent of the respondents use Big Bata analysis for risk mitigation a very low figure. Fraud detection 10% Increased sales Increased market efficiency 29% 29% Other 38%

20 for Big Data Analysis What are the key outcomes of a data analysis within your organization? Base 447 Control Operational Expenditures Ensure Customer Satisfaction Optimize Capital Expenditures Regulatory Compliance Revenue forecasting Product portfolio analysis Mitigate risk Detect and Prevent Fraud Connection between behavior and buying pattern Customer behavior Forecasting Predictive Analytics Customer Clustering Organizational Productivity Process optimization Identify new market opportunities Retain customers Up-sell / Cross-sell to existing clients Other 4% 12% 10% 13% 15% 16% 24% 22% 21% 21% 21% 25% 29% 30% 30% 28% 30% 42% 40% Forecasting and process optimization is among the most desired objectives in the Nordics (42 and 40 percent). Predictive analysis is only an objective for 10 percent and customer clustering only by 4 percent. 20

21 Business Measurement Can you use business metrics or KPIs to measure successful data analytics projects? There are available measurement methods for Big Data analysis, but approximately half of the respondents do not currently measure their projects and Do not know 20% Base 450 activities. This indicates a huge potential for knowledge and practice sharing in the Nordic region. No 31% Yes 49% If no, why? 45% Do not see the use, do not have the need 23% Too complex to measure, difficult to select parameters, lack resources or tools 19% Not today, but working on it and wanting to measure it 14% Unspecified 21

22 Business Measurement Can you use business metrics or KPIs to measure successful data analytics projects (per country) 100% 80% 60% 13% 36% 34% 16% 24% 17% 31% 40% 32% 20% 51% 33% 59% 52% 0% Denmark 76 Finland 90 Norway 91 Sweden 192 Do not know No Yes 22

23 Use of External Consultants Are you using external Big Data consultants? Half of the Nordic organizations use external consultants for various parts of Big Data analysis projects, e.g. ongoing analysis and design and deployment when the project is Do not know 4% Base 450 started. No 45% Yes 51% 23

24 Use of External Consultants If yes, within what areas? Half of the Nordic organizations use external consultants for various parts of Big Data analysis projects, e.g. ongoing analysis and design and deployment when the project is Reporting 22% Project management 23% Base 217 Analysis 47% started. Design and deployment 23% Other 27% Data management 41% 24

25 Technical Solutions What types of data solutions are you using for Big Data analysis? Many of the respondents state that traditional databases are used for Big Data analysis, which indicate that these databases are used mainly for traditional analysis. In-memory databases 9% Column databases 10% Base 432 The results from the survey also show that some of the BI tools are used for traditional analysis. Other 23% Traditional databases 77% BI solution/ front-end tools (e.g. Business Objects) 66% 25

26 Technical Solutions If BI solution, which one? Base 218 Proprietary 8% SAS 5% Cognos 15% QlikView Oracle SAP 20% 18% 24% Microsoft BI 29% Other systems 14%

27 Technical Solutions Are you using special technology such as Hadoop and MapReduce? Yes 5% Do not know 17% Base 444 No 78% Organizations around the word increasingly use special software for Big Data analysis, such as Hadoop and MapReduce. Only 5 percent of the Nordic organizations use special technology, which reflects the low usage of unstructured data analysis. Not yet, but we will use Hadoop and have a started a study project on it. I have never heard anything about these technologies.. 27

28 Technical Solutions How many information systems need to supply data for your Big Data analytics? 0 3% The number of information systems generating information in the Big data analysis varies. For organizations with 7-8 or more information systems, the need for a central Enterprise Data Warehouse (EDW) is crucial % 18% % 7-8 5% % >10 25%

29 Frequencies and Velocity How updated is your information today? 53 percent of the respondents update their information in realtime. But without a central Enterprise Data warehouse, the real-time update is more likely done Daily 15% Base 429 within the separate information systems for e.g. finance, HR, CRM, etc. Hourly 30% Real-time 53% Monthly 31% 29

30 Frequencies and Velocity How often would you like it to be updated? Every minute 16% > a week 17% Hourly 22% 1-2 days 41% Base 409 Real-time 62% 45% It depends on the type of data, adjusted for internal department needs 39% Do not have the need 7% Currently focusing on other areas (e.g. data quality) 5% Unspecified 6% Matter of resources 30

31 Data Volumes How large are the data volumes you manage and analyze today (both structured and unstructured data)? Base 389 Do not know 2% < 1 Tbyte 1 5 Tbyte 24% 26% Nordic organizations store a lot of data on disk and in separate systems. This data is in general not used entirely in the analysis, so there is a huge potential in defining and including all available data in a thorough Big Data analysis Tbyte 12% Tbyte 8% Tbyte Tbyte 4% 10% Tbyte 8% Tbyte 2% > TByte 5%

32 Company SAP Web Site About the survey The survey was conducted in March-April 2012 among CIO s, data warehouse managers, business intelligence professionals, IT managers, etc. The 450 respondents came from Sweden (193), Norway (91), Denmark (76) and Finland (90). The selected organizations are private and governmental all managing large data volumes today. 32

A TECHNICAL WHITE PAPER ATTUNITY VISIBILITY

A TECHNICAL WHITE PAPER ATTUNITY VISIBILITY A TECHNICAL WHITE PAPER ATTUNITY VISIBILITY Analytics for Enterprise Data Warehouse Management and Optimization Executive Summary Successful enterprise data management is an important initiative for growing

More information

Business Analytics and Big Data. Computerworld March 2012 Survey Results

Business Analytics and Big Data. Computerworld March 2012 Survey Results Business Analytics and Big Data Computerworld March 2012 Survey Results Purpose & Methodology Survey Sample Survey Method Field Work 1/24/12-2/21/12 Audience Base Computerworld Online Collection Number

More information

Demonstration of SAP Predictive Analysis 1.0, consumption from SAP BI clients and best practices

Demonstration of SAP Predictive Analysis 1.0, consumption from SAP BI clients and best practices September 10-13, 2012 Orlando, Florida Demonstration of SAP Predictive Analysis 1.0, consumption from SAP BI clients and best practices Vishwanath Belur, Product Manager, SAP Predictive Analysis Learning

More information

SAP Predictive Analysis: Strategy, Value Proposition

SAP Predictive Analysis: Strategy, Value Proposition September 10-13, 2012 Orlando, Florida SAP Predictive Analysis: Strategy, Value Proposition Thomas B Kuruvilla, Solution Management, SAP Business Intelligence Scott Leaver, Solution Management, SAP Business

More information

Business Intelligence. Advanced visualization. Reporting & dashboards. Mobile BI. Packaged BI

Business Intelligence. Advanced visualization. Reporting & dashboards. Mobile BI. Packaged BI Data & Analytics 1 Data & Analytics Solutions - Overview Information Management Business Intelligence Advanced Analytics Data governance Data modeling & architecture Master data management Enterprise data

More information

SAP Solution Brief SAP HANA. Transform Your Future with Better Business Insight Using Predictive Analytics

SAP Solution Brief SAP HANA. Transform Your Future with Better Business Insight Using Predictive Analytics SAP Brief SAP HANA Objectives Transform Your Future with Better Business Insight Using Predictive Analytics Dealing with the new reality Dealing with the new reality Organizations like yours can identify

More information

May 2015 Robert Gibbon & Jochen Stroobants

May 2015 Robert Gibbon & Jochen Stroobants May 2015 Robert Gibbon & Jochen Stroobants 1 Robert Gibbon Founder at Big Industries Technical solution architect Hands on knowledge of Big Data design, build and operation Hadoop guru Jochen Stroobants

More information

Business Analytics and the Nexus of Information

Business Analytics and the Nexus of Information Business Analytics and the Nexus of Information 2 The Impact of the Nexus of Forces 4 From the Gartner Files: Information and the Nexus of Forces: Delivering and Analyzing Data 6 About IBM Business Analytics

More information

SOCIAL MEDIA AND BUSINESS INTELLIGENCE SURVEY RESULTS & ANALYSIS CONDUCTED JANUARY FEBRUARY 2012

SOCIAL MEDIA AND BUSINESS INTELLIGENCE SURVEY RESULTS & ANALYSIS CONDUCTED JANUARY FEBRUARY 2012 SOCIAL MEDIA AND BUSINESS INTELLIGENCE SURVEY RESULTS & ANALYSIS CONDUCTED JANUARY FEBRUARY 2012 By Peter J. Auditore Produced by Unisphere Research, a Division of Information Today, Inc. March 2012 Sponsored

More information

Overview, Goals, & Introductions

Overview, Goals, & Introductions Improving the Retail Experience with Predictive Analytics www.spss.com/perspectives Overview, Goals, & Introductions Goal: To present the Retail Business Maturity Model Equip you with a plan of attack

More information

Zero-in on business decisions through innovation solutions for smart big data management. How to turn volume, variety and velocity into value

Zero-in on business decisions through innovation solutions for smart big data management. How to turn volume, variety and velocity into value Zero-in on business decisions through innovation solutions for smart big data management How to turn volume, variety and velocity into value ON THE LOOKOUT FOR NEW SOURCES OF VALUE CREATION WHAT WILL DRIVE

More information

Getting Value from Big Data with Analytics

Getting Value from Big Data with Analytics Getting Value from Big Data with Analytics Edward Roske, CEO Oracle ACE Director info@interrel.com BLOG: LookSmarter.blogspot.com WEBSITE: www.interrel.com TWITTER: Eroske About interrel Reigning Oracle

More information

PDF PREVIEW EMERGING TECHNOLOGIES. Applying Technologies for Social Media Data Analysis

PDF PREVIEW EMERGING TECHNOLOGIES. Applying Technologies for Social Media Data Analysis VOLUME 34 BEST PRACTICES IN BUSINESS INTELLIGENCE AND DATA WAREHOUSING FROM LEADING SOLUTION PROVIDERS AND EXPERTS PDF PREVIEW IN EMERGING TECHNOLOGIES POWERFUL CASE STUDIES AND LESSONS LEARNED FOCUSING

More information

How To Use Big Data Effectively

How To Use Big Data Effectively Why is BIG Data Important? March 2012 1 Why is BIG Data Important? A Navint Partners White Paper May 2012 Why is BIG Data Important? March 2012 2 What is Big Data? Big data is a term that refers to data

More information

Evaluation Guide. Call Center Operations and SLA Monitoring Performance Blueprint

Evaluation Guide. Call Center Operations and SLA Monitoring Performance Blueprint Evaluation Guide Call Center Operations and SLA Monitoring Performance Blueprint Achieving real-time efficiencies and enhanced customer satisfaction in call center operations Corporate frontlines are experiencing

More information

COULD VS. SHOULD: BALANCING BIG DATA AND ANALYTICS TECHNOLOGY WITH PRACTICAL OUTCOMES

COULD VS. SHOULD: BALANCING BIG DATA AND ANALYTICS TECHNOLOGY WITH PRACTICAL OUTCOMES COULD VS. SHOULD: BALANCING BIG DATA AND ANALYTICS TECHNOLOGY The business world is abuzz with the potential of data. In fact, most businesses have so much data that it is difficult for them to process

More information

Achieving Business Value through Big Data Analytics Philip Russom

Achieving Business Value through Big Data Analytics Philip Russom Achieving Business Value through Big Data Analytics Philip Russom TDWI Research Director for Data Management October 3, 2012 Sponsor 2 Speakers Philip Russom Research Director, Data Management, TDWI Brian

More information

QLIKVIEW DEPLOYMENT FOR BIG DATA ANALYTICS AT KING.COM

QLIKVIEW DEPLOYMENT FOR BIG DATA ANALYTICS AT KING.COM QLIKVIEW DEPLOYMENT FOR BIG DATA ANALYTICS AT KING.COM QlikView Technical Case Study Series Big Data June 2012 qlikview.com Introduction This QlikView technical case study focuses on the QlikView deployment

More information

Big Data and Analytics in Government

Big Data and Analytics in Government Big Data and Analytics in Government Nov 29, 2012 Mark Johnson Director, Engineered Systems Program 2 Agenda What Big Data Is Government Big Data Use Cases Building a Complete Information Solution Conclusion

More information

SAP BusinessObjects. Solutions for Large Enterprises & SME s

SAP BusinessObjects. Solutions for Large Enterprises & SME s SAP BusinessObjects Solutions for Large Enterprises & SME s Since 1993, we have been using our BI experience to ensure you buy the right licences at the lowest price, thus helping to deliver the best and

More information

5 Big Data Use Cases to Understand Your Customer Journey CUSTOMER ANALYTICS EBOOK

5 Big Data Use Cases to Understand Your Customer Journey CUSTOMER ANALYTICS EBOOK 5 Big Data Use Cases to Understand Your Customer Journey CUSTOMER ANALYTICS EBOOK CUSTOMER JOURNEY Technology is radically transforming the customer journey. Today s customers are more empowered and connected

More information

WHITEPAPER. Creating and Deploying Predictive Strategies that Drive Customer Value in Marketing, Sales and Risk

WHITEPAPER. Creating and Deploying Predictive Strategies that Drive Customer Value in Marketing, Sales and Risk WHITEPAPER Creating and Deploying Predictive Strategies that Drive Customer Value in Marketing, Sales and Risk Overview Angoss is helping its clients achieve significant revenue growth and measurable return

More information

How to make BIG DATA work for you. Faster results with Microsoft SQL Server PDW

How to make BIG DATA work for you. Faster results with Microsoft SQL Server PDW How to make BIG DATA work for you. Faster results with Microsoft SQL Server PDW Roger Breu PDW Solution Specialist Microsoft Western Europe Marcus Gullberg PDW Partner Account Manager Microsoft Sweden

More information

Data Maturity Survey in Financial Services

Data Maturity Survey in Financial Services Percent of Responses Data Maturity Survey in Financial Services June 29, 2015 Executive Summary PanoVista.co LLC is conducting a high level, indicative survey regarding the maturity and future state of

More information

Big Data Integration: A Buyer's Guide

Big Data Integration: A Buyer's Guide SEPTEMBER 2013 Buyer s Guide to Big Data Integration Sponsored by Contents Introduction 1 Challenges of Big Data Integration: New and Old 1 What You Need for Big Data Integration 3 Preferred Technology

More information

Architecting your Business for Big Data Your Bridge to a Modern Information Architecture

Architecting your Business for Big Data Your Bridge to a Modern Information Architecture Architecting your Business for Big Data Your Bridge to a Modern Information Architecture Robert Stackowiak Vice President, Information Architecture & Big Data Oracle Safe Harbor Statement The following

More information

Marketing Analytics Technology Overview

Marketing Analytics Technology Overview Marketing Analytics Technology Overview Disclaimer: All logos, photos, etc. used in this presentation are the property of their respective copyright owners and are used here for educational purposes only

More information

Top 10 Trends In Business Intelligence for 2007

Top 10 Trends In Business Intelligence for 2007 W H I T E P A P E R Top 10 Trends In Business Intelligence for 2007 HP s New Information Management Practice Table of contents Trend #1: BI Governance: Ensuring the Effectiveness of Programs and Investments

More information

Advanced Big Data Analytics with R and Hadoop

Advanced Big Data Analytics with R and Hadoop REVOLUTION ANALYTICS WHITE PAPER Advanced Big Data Analytics with R and Hadoop 'Big Data' Analytics as a Competitive Advantage Big Analytics delivers competitive advantage in two ways compared to the traditional

More information

Endeca Introduction to Big Data Analytics

Endeca Introduction to Big Data Analytics Endeca Introduction to Big Data Analytics Overview May 8, 2013 1 Agenda Introduction Overview Analytics for Big Data Overview Endeca Information Discovery Q & A 2 Introduction Business vs. IT Big Data

More information

Apache Hadoop Patterns of Use

Apache Hadoop Patterns of Use Community Driven Apache Hadoop Apache Hadoop Patterns of Use April 2013 2013 Hortonworks Inc. http://www.hortonworks.com Big Data: Apache Hadoop Use Distilled There certainly is no shortage of hype when

More information

The 3 questions to ask yourself about BIG DATA

The 3 questions to ask yourself about BIG DATA The 3 questions to ask yourself about BIG DATA Do you have a big data problem? Companies looking to tackle big data problems are embarking on a journey that is full of hype, buzz, confusion, and misinformation.

More information

Analytics for Business, Consumers and Social Insights

Analytics for Business, Consumers and Social Insights Singapore Management University Institutional Knowledge at Singapore Management University Library Events SMU Library 7-2015 Analytics for Business, Consumers and Social Insights Bhavish SOOD Gartner Follow

More information

Reduce and manage operating costs and improve efficiency. Support better business decisions based on availability of real-time information

Reduce and manage operating costs and improve efficiency. Support better business decisions based on availability of real-time information Data Management Solutions Horizon Software Solution s Data Management Solutions provide organisations with confidence in control of their data as they change systems and implement new solutions. Data is

More information

QlikView in Banking How and why many worlds leading banks are using QlikView

QlikView in Banking How and why many worlds leading banks are using QlikView QlikView in Banking How and why many worlds leading banks are using QlikView September 2013 Duncan Ash / Mike Saliter / Paul Van Siclen Common Banking Challenges Branch Managers / Financial Advisors /

More information

Empower Your organization with

Empower Your organization with Empower Your organization with Big Data Predictive Analytics Solutions AUTOMOBILES MACHINE DATA POINT SALE SOCIAL NET WORK RFID CUSTOMER BASED TEXT DATA SMART METER MOBILE DATA LOCATION BASED STRUCTURED

More information

Applied Business Intelligence. Iakovos Motakis, Ph.D. Director, DW & Decision Support Systems Intrasoft SA

Applied Business Intelligence. Iakovos Motakis, Ph.D. Director, DW & Decision Support Systems Intrasoft SA Applied Business Intelligence Iakovos Motakis, Ph.D. Director, DW & Decision Support Systems Intrasoft SA Agenda Business Drivers and Perspectives Technology & Analytical Applications Trends Challenges

More information

Key Considerations for a Successful Deployment of Real Time Analytics July 23, 2014

Key Considerations for a Successful Deployment of Real Time Analytics July 23, 2014 Key Considerations for a Successful Deployment of Real Time Analytics July 23, 2014 Brought to you by Vivit Big Data Special Interest Group led by Kate Fontanella, Pramod Singh, Akshar Dave, Abdul B. Rafi,

More information

An Integrated Big Data & Analytics Infrastructure June 14, 2012 Robert Stackowiak, VP Oracle ESG Data Systems Architecture

An Integrated Big Data & Analytics Infrastructure June 14, 2012 Robert Stackowiak, VP Oracle ESG Data Systems Architecture An Integrated Big Data & Analytics Infrastructure June 14, 2012 Robert Stackowiak, VP ESG Data Systems Architecture Big Data & Analytics as a Service Components Unstructured Data / Sparse Data of Value

More information

Comparative Analysis of the Main Business Intelligence Solutions

Comparative Analysis of the Main Business Intelligence Solutions 148 Informatica Economică vol. 17, no. 2/2013 Comparative Analysis of the Main Business Intelligence Solutions Alexandra RUSANEANU Faculty of Cybernetics, Statistics and Economic Informatics Bucharest

More information

ABOUT US WHO WE ARE. Helping you succeed against the odds...

ABOUT US WHO WE ARE. Helping you succeed against the odds... ACCURACY DELIVERED ABOUT US WHO WE ARE BizAcuity is a fast growing Business intelligence strategy company, providing reliable, scalable and cost effective consultancy and services to clients across the

More information

Chapter 6 8/12/2015. Foundations of Business Intelligence: Databases and Information Management. Problem:

Chapter 6 8/12/2015. Foundations of Business Intelligence: Databases and Information Management. Problem: Foundations of Business Intelligence: Databases and Information Management VIDEO CASES Chapter 6 Case 1a: City of Dubuque Uses Cloud Computing and Sensors to Build a Smarter, Sustainable City Case 1b:

More information

2015 Analyst and Advisor Summit. Advanced Data Analytics Dr. Rod Fontecilla Vice President, Application Services, Chief Data Scientist

2015 Analyst and Advisor Summit. Advanced Data Analytics Dr. Rod Fontecilla Vice President, Application Services, Chief Data Scientist 2015 Analyst and Advisor Summit Advanced Data Analytics Dr. Rod Fontecilla Vice President, Application Services, Chief Data Scientist Agenda Key Facts Offerings and Capabilities Case Studies When to Engage

More information

High-Performance Analytics

High-Performance Analytics High-Performance Analytics David Pope January 2012 Principal Solutions Architect High Performance Analytics Practice Saturday, April 21, 2012 Agenda Who Is SAS / SAS Technology Evolution Current Trends

More information

Predictive Marketing for Banking

Predictive Marketing for Banking Tony Firmani Predictive Analytics Solution Architect Predictive Marketing for Banking Business Analytics software Session Overview Data Drives Decisions Applying Predictive Analytics Throughout Entire

More information

Information-Driven Transformation in Retail with the Enterprise Data Hub Accelerator

Information-Driven Transformation in Retail with the Enterprise Data Hub Accelerator Introduction Enterprise Data Hub Accelerator Retail Sector Use Cases Capabilities Information-Driven Transformation in Retail with the Enterprise Data Hub Accelerator Introduction Enterprise Data Hub Accelerator

More information

<Insert Picture Here> The Age of the Pure Play BI Vendor is Over

<Insert Picture Here> The Age of the Pure Play BI Vendor is Over The Age of the Pure Play BI Vendor is Over Simon Miller Principal Sales Consultant Oracle BI & Analytics The Business Intelligence Marketplace $12B $10B $8B $6B $4B $2B 0 $11.1B Market

More information

The Definitive Guide to Data Blending. White Paper

The Definitive Guide to Data Blending. White Paper The Definitive Guide to Data Blending White Paper Leveraging Alteryx Analytics for data blending you can: Gather and blend data from virtually any data source including local, third-party, and cloud/ social

More information

Vendor briefing Business Intelligence and Analytics Platforms Gartner 15 capabilities

Vendor briefing Business Intelligence and Analytics Platforms Gartner 15 capabilities Vendor briefing Business Intelligence and Analytics Platforms Gartner 15 capabilities April, 2013 gaddsoftware.com Table of content 1. Introduction... 3 2. Vendor briefings questions and answers... 3 2.1.

More information

C A S E S T UDY The Path Toward Pervasive Business Intelligence at an Asian Telecommunication Services Provider

C A S E S T UDY The Path Toward Pervasive Business Intelligence at an Asian Telecommunication Services Provider C A S E S T UDY The Path Toward Pervasive Business Intelligence at an Asian Telecommunication Services Provider Sponsored by: Tata Consultancy Services November 2008 SUMMARY Global Headquarters: 5 Speen

More information

Predicting win/loss probabilities with pipeline data Model uses SAS, HPE Vertica, QlikView for sales opportunity predictive analytics

Predicting win/loss probabilities with pipeline data Model uses SAS, HPE Vertica, QlikView for sales opportunity predictive analytics Case Study Objective Provide a method to identify which quarterly sales opportunities are most likely to close successfully or not. Predicting win/loss probabilities with pipeline data Model uses SAS,

More information

How To Use Social Media To Improve Your Business

How To Use Social Media To Improve Your Business IBM Software Business Analytics Social Analytics Social Business Analytics Gaining business value from social media 2 Social Business Analytics Contents 2 Overview 3 Analytics as a competitive advantage

More information

HROUG. The future of Business Intelligence & Enterprise Performance Management. Rovinj October 18, 2007

HROUG. The future of Business Intelligence & Enterprise Performance Management. Rovinj October 18, 2007 HROUG Rovinj October 18, 2007 The future of Business Intelligence & Enterprise Performance Management Alexander Meixner Sales Executive, BI/EPM, South East Europe Oracle s Product

More information

Toronto 26 th SAP BI. Leap Forward with SAP

Toronto 26 th SAP BI. Leap Forward with SAP Toronto 26 th SAP BI Leap Forward with SAP Business Intelligence SAP BI 4.0 and SAP BW Operational BI with SAP ERP SAP HANA and BI Operational vs Decision making reporting Verify the evolution of the KPIs,

More information

Big Data (Adv. Analytics) in 15 Mins. Peter LePine Managing Director Sales Support IM & BI Practice

Big Data (Adv. Analytics) in 15 Mins. Peter LePine Managing Director Sales Support IM & BI Practice Big Data (Adv. Analytics) in 15 Mins. Peter LePine Managing Director Sales Support IM & BI Practice Agenda Big Data in 15 Mins. Goal: Provide a basic understanding of; What is Big Data; Why it s important

More information

Forecast of Big Data Trends. Assoc. Prof. Dr. Thanachart Numnonda Executive Director IMC Institute 3 September 2014

Forecast of Big Data Trends. Assoc. Prof. Dr. Thanachart Numnonda Executive Director IMC Institute 3 September 2014 Forecast of Big Data Trends Assoc. Prof. Dr. Thanachart Numnonda Executive Director IMC Institute 3 September 2014 Big Data transforms Business 2 Data created every minute Source http://mashable.com/2012/06/22/data-created-every-minute/

More information

Understanding the Development and Use of Analytical Business Intelligence Applications

Understanding the Development and Use of Analytical Business Intelligence Applications Understanding the Development and Use of Analytical Business Intelligence Applications By Elliot King, Ph.D Professor of Communication Lattanze Center Loyola University Maryland Table of Contents Introduction...1

More information

Dynamic Enterprise Performance Management

Dynamic Enterprise Performance Management TM Dynamic Enterprise Performance Management Data. Insights. Action. 1 Pull insight out of the chaos Chaos. It s a word that few CFOs would like associated with their businesses; but when it comes to decision

More information

Data Virtualization A Potential Antidote for Big Data Growing Pains

Data Virtualization A Potential Antidote for Big Data Growing Pains perspective Data Virtualization A Potential Antidote for Big Data Growing Pains Atul Shrivastava Abstract Enterprises are already facing challenges around data consolidation, heterogeneity, quality, and

More information

Big Data & the Cloud: The Sum Is Greater Than the Parts

Big Data & the Cloud: The Sum Is Greater Than the Parts E-PAPER March 2014 Big Data & the Cloud: The Sum Is Greater Than the Parts Learn how to accelerate your move to the cloud and use big data to discover new hidden value for your business and your users.

More information

Mike Maxey. Senior Director Product Marketing Greenplum A Division of EMC. Copyright 2011 EMC Corporation. All rights reserved.

Mike Maxey. Senior Director Product Marketing Greenplum A Division of EMC. Copyright 2011 EMC Corporation. All rights reserved. Mike Maxey Senior Director Product Marketing Greenplum A Division of EMC 1 Greenplum Becomes the Foundation of EMC s Big Data Analytics (July 2010) E M C A C Q U I R E S G R E E N P L U M For three years,

More information

Grabbing Value from Big Data: Mining for Diamonds in Financial Services

Grabbing Value from Big Data: Mining for Diamonds in Financial Services Financial Services Grabbing Value from Big Data: Mining for Diamonds in Financial Services How financial services companies can harness the innovative power of big data 2 Grabbing Value from Big Data:

More information

NEEDLE STACKS & BIG DATA: USING EVENT STREAM PROCESSING FOR RISK, SURVEILLANCE & SECURITY ANALYTICS IN CAPITAL MARKETS

NEEDLE STACKS & BIG DATA: USING EVENT STREAM PROCESSING FOR RISK, SURVEILLANCE & SECURITY ANALYTICS IN CAPITAL MARKETS NEEDLE STACKS & BIG DATA: USING PROCESSING FOR RISK, SURVEILLANCE & SECURITY ANALYTICS IN CAPITAL MARKETS JERRY BAULIER, DIRECTOR, PROCESSING DAVID M. WALLACE, GLOBAL FINANCIAL SERVICES MARKETING MANAGER

More information

Business Intelligence. A Presentation of the Current Lead Solutions and a Comparative Analysis of the Main Providers

Business Intelligence. A Presentation of the Current Lead Solutions and a Comparative Analysis of the Main Providers 60 Business Intelligence. A Presentation of the Current Lead Solutions and a Comparative Analysis of the Main Providers Business Intelligence. A Presentation of the Current Lead Solutions and a Comparative

More information

Oracle Business Intelligence Applications Overview. An Oracle White Paper March 2007

Oracle Business Intelligence Applications Overview. An Oracle White Paper March 2007 Oracle Business Intelligence Applications Overview An Oracle White Paper March 2007 Note: The following is intended to outline our general product direction. It is intended for information purposes only,

More information

The big data business model: opportunity and key success factors

The big data business model: opportunity and key success factors MENA Summit 2013: Enabling innovation, driving profitability The big data business model: opportunity and key success factors 6 November 2013 Justin van der Lande EVENT PARTNERS: 2 Introduction What is

More information

perspective Big Data Analytics: It s Transformational Impact on the Insurance Industry Abstract

perspective Big Data Analytics: It s Transformational Impact on the Insurance Industry Abstract perspective Big Data Analytics: It s Transformational Impact on the Insurance Industry Abstract The insurance industry runs on data, and the success of its business model is based on analyzing data to

More information

ElegantJ BI. White Paper. The Competitive Advantage of Business Intelligence (BI) Forecasting and Predictive Analysis

ElegantJ BI. White Paper. The Competitive Advantage of Business Intelligence (BI) Forecasting and Predictive Analysis ElegantJ BI White Paper The Competitive Advantage of Business Intelligence (BI) Forecasting and Predictive Analysis Integrated Business Intelligence and Reporting for Performance Management, Operational

More information

9 Reasons Your Product Needs. Better Analytics. A Visual Guide

9 Reasons Your Product Needs. Better Analytics. A Visual Guide 9 Reasons Your Product Needs Better Analytics 02 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 A Visual Guide Better Analytics for Your Users Table of Contents Introduction... 2 As a product

More information

PREDICTIVE ANALYTICS IN HIGHER EDUCATION NOVEMBER 6, 2014

PREDICTIVE ANALYTICS IN HIGHER EDUCATION NOVEMBER 6, 2014 PREDICTIVE ANALYTICS IN HIGHER EDUCATION NOVEMBER 6, 2014 WHAT IS PREDICTIVE ANALYTICS? Predictive Analytics helps connect data to effective action by drawing reliable conclusions about current conditions

More information

QAD Business Intelligence

QAD Business Intelligence QAD Business Intelligence QAD Business Intelligence (QAD BI) unifies data from multiple sources across the enterprise and provides a complete solution that enables key enterprise decision makers to access,

More information

Tap into Big Data at the Speed of Business

Tap into Big Data at the Speed of Business SAP Brief SAP Technology SAP Sybase IQ Objectives Tap into Big Data at the Speed of Business A simpler, more affordable approach to Big Data analytics A simpler, more affordable approach to Big Data analytics

More information

QLIKVIEW IN THE ENTERPRISE

QLIKVIEW IN THE ENTERPRISE QLIKVIEW IN THE ENTERPRISE IT Overview The QlikView Business Discovery platform is a natural fit within an organization s Information Architecture, allowing IT and BI groups to serve the ever-growing analytical

More information

The Enterprise Data Hub and The Modern Information Architecture

The Enterprise Data Hub and The Modern Information Architecture The Enterprise Data Hub and The Modern Information Architecture Dr. Amr Awadallah CTO & Co-Founder, Cloudera Twitter: @awadallah 1 2013 Cloudera, Inc. All rights reserved. Cloudera Overview The Leader

More information

Practical Considerations for Real-Time Business Intelligence. Donovan Schneider Yahoo! September 11, 2006

Practical Considerations for Real-Time Business Intelligence. Donovan Schneider Yahoo! September 11, 2006 Practical Considerations for Real-Time Business Intelligence Donovan Schneider Yahoo! September 11, 2006 Outline Business Intelligence (BI) Background Real-Time Business Intelligence Examples Two Requirements

More information

Alexander Nikov. 5. Database Systems and Managing Data Resources. Learning Objectives. RR Donnelley Tries to Master Its Data

Alexander Nikov. 5. Database Systems and Managing Data Resources. Learning Objectives. RR Donnelley Tries to Master Its Data INFO 1500 Introduction to IT Fundamentals 5. Database Systems and Managing Data Resources Learning Objectives 1. Describe how the problems of managing data resources in a traditional file environment are

More information

Nordic Executive Survey THEME 2014: THE PARADIGM SHIFT

Nordic Executive Survey THEME 2014: THE PARADIGM SHIFT Nordic Executive Survey THEME 2014: THE PARADIGM SHIFT Nordic Executive Survey 2014 The Paradigm Shift 2 Introduction For the second time, Hammer & Hanborg present the results from the Nordic Executive

More information

Mind Commerce. http://www.marketresearch.com/mind Commerce Publishing v3122/ Publisher Sample

Mind Commerce. http://www.marketresearch.com/mind Commerce Publishing v3122/ Publisher Sample Mind Commerce http://www.marketresearch.com/mind Commerce Publishing v3122/ Publisher Sample Phone: 800.298.5699 (US) or +1.240.747.3093 or +1.240.747.3093 (Int'l) Hours: Monday - Thursday: 5:30am - 6:30pm

More information

The Next Wave of Data Management. Is Big Data The New Normal?

The Next Wave of Data Management. Is Big Data The New Normal? The Next Wave of Data Management Is Big Data The New Normal? Table of Contents Introduction 3 Separating Reality and Hype 3 Why Are Firms Making IT Investments In Big Data? 4 Trends In Data Management

More information

Integrating SAP and non-sap data for comprehensive Business Intelligence

Integrating SAP and non-sap data for comprehensive Business Intelligence WHITE PAPER Integrating SAP and non-sap data for comprehensive Business Intelligence www.barc.de/en Business Application Research Center 2 Integrating SAP and non-sap data Authors Timm Grosser Senior Analyst

More information

The Future of Business Analytics is Now! 2013 IBM Corporation

The Future of Business Analytics is Now! 2013 IBM Corporation The Future of Business Analytics is Now! 1 The pressures on organizations are at a point where analytics has evolved from a business initiative to a BUSINESS IMPERATIVE More organization are using analytics

More information

Taking A Proactive Approach To Loyalty & Retention

Taking A Proactive Approach To Loyalty & Retention THE STATE OF Customer Analytics Taking A Proactive Approach To Loyalty & Retention By Kerry Doyle An Exclusive Research Report UBM TechWeb research conducted an online study of 339 marketing professionals

More information

Business Intelligence (BI) Data Store Project Discussion / Draft Outline for Requirements Document

Business Intelligence (BI) Data Store Project Discussion / Draft Outline for Requirements Document Business Intelligence (BI) Data Store Project Discussion / Draft Outline for Requirements Document Approval Contacts Sign-off Copy Distribution (List of Names) Revision History Definitions (Organization

More information

Cost-Effective Business Intelligence with Red Hat and Open Source

Cost-Effective Business Intelligence with Red Hat and Open Source Cost-Effective Business Intelligence with Red Hat and Open Source Sherman Wood Director, Business Intelligence, Jaspersoft September 3, 2009 1 Agenda Introductions Quick survey What is BI?: reporting,

More information

1 Performance Moves to the Forefront for Data Warehouse Initiatives. 2 Real-Time Data Gets Real

1 Performance Moves to the Forefront for Data Warehouse Initiatives. 2 Real-Time Data Gets Real Top 10 Data Warehouse Trends for 2013 What are the most compelling trends in storage and data warehousing that motivate IT leaders to undertake new initiatives? Which ideas, solutions, and technologies

More information

SAP Predictive Analytics

SAP Predictive Analytics SAP Predictive Analytics What s the best that COULD happen? Bringing predictive analytics to the end user SAP Forum Belgium September 9, 2015 Waldemar Adams @adamsw SVP & GM Analytics SAP Europe, Middle-East

More information

SAP Predictive Analysis: Strategy, Value Proposition

SAP Predictive Analysis: Strategy, Value Proposition September 10-13, 2012 Orlando, Florida SAP Predictive Analysis: Strategy, Value Proposition Charles Gadalla, Solution Management, SAP Business Intelligence Manavendra Misra, Chief Knowledge Officer, Cognilytics

More information

BIG DATA I N B A N K I N G

BIG DATA I N B A N K I N G $ BIG DATA IN BANKING Table of contents What is Big Data?... How data science creates value in Banking... Best practices for Banking. Case studies... 3 7 10 1. Fraud detection... 2. Contact center efficiency

More information

BIG DATA. Value 8/14/2014 WHAT IS BIG DATA? THE 5 V'S OF BIG DATA WHAT IS BIG DATA?

BIG DATA. Value 8/14/2014 WHAT IS BIG DATA? THE 5 V'S OF BIG DATA WHAT IS BIG DATA? WHAT IS BIG DATA? BIG DATA DR. KLARA NELSON THE UNIVERSITY OF TAMPA "Volumes of data that are unusually large, or types of data that are unstructured" Thomas Davenport, Keeping Up with the Quants, 2013,

More information

Foundations of Business Intelligence: Databases and Information Management

Foundations of Business Intelligence: Databases and Information Management Foundations of Business Intelligence: Databases and Information Management Wienand Omta Fabiano Dalpiaz 1 drs. ing. Wienand Omta Learning Objectives Describe how the problems of managing data resources

More information

Introduction to Predictive Analytics: SPSS Modeler

Introduction to Predictive Analytics: SPSS Modeler Introduction to Predictive Analytics: SPSS Modeler John Antonucci, Sr. BDM Katrina Adams Ph.D. Welcome! The Webinar will begin at 12:00 pm EST LPA Events Calendar Upcoming Webinars Today - Introduction

More information

The Four Components of HCL s Business Planning Accelerator for Insurance

The Four Components of HCL s Business Planning Accelerator for Insurance The Problem In today s dynamic insurance industry, business planning is no longer just an operational necessity; it is a competitive differentiator. It needs to be fast, it needs to be accurate and it

More information

Business Intelligence / Big Data Consulting Service

Business Intelligence / Big Data Consulting Service Business Intelligence / Big Data Consulting Service DATASHEET Business Problem Enterprises and IT businesses have been accumulating an enormous amount of data for years (according to IDC data is growing

More information

Digital Analytics Checkup:

Digital Analytics Checkup: Digital Analytics Checkup: How to evaluate the impact of your web analytics data A Digital Marketing Depot White Paper Executive Summary Marketing organizations are being inundated with a greater volume,

More information

Understanding the Value of In-Memory in the IT Landscape

Understanding the Value of In-Memory in the IT Landscape February 2012 Understing the Value of In-Memory in Sponsored by QlikView Contents The Many Faces of In-Memory 1 The Meaning of In-Memory 2 The Data Analysis Value Chain Your Goals 3 Mapping Vendors to

More information

Top 10 Predictive Use Cases and Customer Case Studies

Top 10 Predictive Use Cases and Customer Case Studies Top 10 Predictive Use Cases and Customer Case Studies Confidently anticipate and drive better business outcomes Pierre Leroux, Director Predictive Analytics 2015 SAP SE or an SAP affiliate company. All

More information

Aligning Your Strategic Initiatives with a Realistic Big Data Analytics Roadmap

Aligning Your Strategic Initiatives with a Realistic Big Data Analytics Roadmap Aligning Your Strategic Initiatives with a Realistic Big Data Analytics Roadmap 3 key strategic advantages, and a realistic roadmap for what you really need, and when 2012, Cognizant Topics to be discussed

More information

Are You Big Data Ready?

Are You Big Data Ready? ACS 2015 Annual Canberra Conference Are You Big Data Ready? Vladimir Videnovic Business Solutions Director Oracle Big Data and Analytics Introduction Introduction What is Big Data? If you can't explain

More information

Big Data in Retail Big Data Analytics Central to Customer Acquisition and Retention Strategies in Retail

Big Data in Retail Big Data Analytics Central to Customer Acquisition and Retention Strategies in Retail Big Data in Retail Big Data Analytics Central to Customer Acquisition and Retention Strategies in Retail MAA7-67 September 2014 Contents Section Slide Numbers Executive Summary 4 Methodology 6 Fundamentals

More information