Welcome to the webinar! ! Even more data in 2014? How to use it to your advantage. The webinar will begin shortly. During the presentation, all lines will be automatically set to silent. Please use the Question dialog box to ask questions, so we can answer them at the end of the webinar. Einwahlnummern: (gebührenpflichtig) Deutschland: +49 (0) 811 8899 6949 Österreich: +43 (0) 7 2088 2866 Schweiz: +41 (0) 225 1813 21 PLEASE USE THE QUESTION FUNCTION TO ASK QUESTIONS 2 AGENDA ! 1. Brief introduction to datavirtuality 2. Challenges in using traditional data warehouse technologies 3. Introduction to the revolutionary, automated data warehouse 4. Front ends: Full flexibility combined with datavirtuality – Example: Tableau as a high-end front-end solution 5. Live-demo 6. Q&A 3 INTRODUCTION - YOUR PRESENTERS Dr. Nick Golovin Founder and CEO of datavirtuality Alex Klebeck Founder and CTO at datavirtuality Philipp Hackländer Founder and Head of Bus. Development at datavirtuality 4 BRIEF INTRODUCTION TO DATAVIRTUALITY DATA VIRTUALITY - THE COMPANY • A young company, 2 years old • Located in Leipzig, Germany • Created out of a research project at the University of Leipzig (Prof. Dr. Erhard Rahm – Institute for IT/Database department; globally, among the best in research) • Employees: 14 • Management: • Dr. Nick Golovin (CEO, chief executive) • Alex Klebeck (CTO, technology and development) • Philipp Hackländer (CSO, sales and finances) • Project idea honored at Data Days 2012, among other venues • Reference clients: 6 CHALLENGES OF TRADITIONAL DATA WAREHOUSE SOLUTIONS New Year’s Resolutions for 2014? 2013’s old problems have just become 2014’s new problems: • Some important data is just not available • Progress on the IT roadmap is slow • Interfaces have to be manually programmed • Most reports are clumsy and slow • There are too few users who can understand and use the data model • Ad hoc reports are either not accessible at all, or only very slowly • Business Intelligence is months (years?) behind the business • Despite lots of plans, often no unified numerical or KPI view in most enterprises 8 THE CHALLENGE: NO OVERVIEW AND NO CONTROL OF THE DATA 1) More and more diverse systems and data formats 2) Increasingly, numerous good front ends in the market Excel Web/ SQL 9 THE CHALLENGE: NO OVERVIEW AND NO CONTROL OF THE DATA 1) Ever more diverse systems and data formats 2) Increasingly, numerous good front ends in the market 3) The issue of interfaces 4) How do I get a unified view? ? ? ? ? ? ? Excel Web/ SQL 10 TRADITIONAL DATA WAREHOUSE PROJECTS Manually setting up the data warehouse often takes very long in practice and is very expensive and prone to error. The classic solution... …is a manual DWH …but the setup is: - complex - time-consuming - very expensive - inflexible - and expensive when in productive operation 11 THE REVOLUTION: AN AUTOMATED, SELF-LEARNING DATA WAREHOUSE APPROX. 80% LESS TIME/EFFORT REQUIRED WITH DATAVIRTUALITY Resource use Process phases Traditional DWH projects Define requirements Develop the concept Develop the solution Test and integrate the solution Connect source systems Connect front ends and build/ use reports DWH project with Productive work Check DWHstructure and adapt it Up to 80% savings in cost and time 13 Productive work AUTOMATED, SELF-LEARNING DATA WAREHOUSE DATA SOURCES DWH Da Step 1: 3: 2: Intermediate Anschließen User können der storage is der Datenquellen bereits mit optimized Arbeit beginnen automatically ta Info on Step 4: Open database types FRONT ENDS ongoing management Excel SQL Dat a Data …and many other data sources …and many other front ends 14 COMPATIBLE WITH ALL FRONT ENDS Tableau example: High end front end with visual intelligence LIVE-DEMO APPROX. 80% LESS TIME/EFFORT WITH DATAVIRTUALITY Resource use Process phases Traditional DWH projects Define requirements Develop the concept Develop the solution Test and integrate the solution Connect source systems Connect front ends and build/ use reports DWH project with Productive work Check and potentially adapt DHW structure Up to 80% savings in cost and time 18 Productive work Salesperson SalesPersonID FirstName MiddleName LastName DepartmentName TerritoryName Customer CustomerID FirstName MiddleName LastName CustomerType City PostalCode StateProvinceID CountryRegionCod e TerritoryName ProductID ProductName ProductNumber ProductSubcategoryName ProductCategoryName StartDate EndDate StandardCost Sales DateID CustomerID SalesPersonID TerritoryID ProductID Quantity GrossRevenue Discount NetRevenue Territory TerritoryID TerritoryName Store MySQL MongoDB MS SQL PostgreSQL Oracle Product StoreID CustomerID StoreName NumberOfEmployee s Time DateID CalendarYear CalendarQuarter CalendarMonth CalendarMonthName CalendarWeek CalendarDayName CalendarDayOfMonth CalendarDayOfWeek CalendarDayOfYear 19 AND NOW IT IS YOUR TURN... ANY QUESTIONS? THANK YOU! YOUR TEAM