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Current business intelligence trends


1 Current Business Intelligence Trends BI trends from the point of view of Infomotion GmbH Tim Kretzschmar Sebastian Schade

2 Agenda Presentation of Business Intelligence Trends Entry at Infomotion


4 Brief profile Sebastian Schade Diploma Business IT specialist Infomotion GmbH Professional Consultant Business Intelligence Dual studies: WS 2003: FSU Jena Wirtschaftsinformatik 03/2008: Degree Bachelor of Science Main topics Consulting: Data modeling ETL DV and technical conception Business Objects Data Services (BODS) Microsoft SQL Server Integration Services (SSIS) Oracle Warehouse Builder (OWB) Pentaho Data Integrator (PDI) Professional background: 2007 today: Infomotion GmbH Consultant Business Objects XI Oracle 10g / 11g Microsoft SQL Server R

5 Brief profile Tim Kretzschmar Infomotion GmbH Consultant Business Intelligence Double degree: 2003: Johann-Wolfgang-Goethe University Frankfurt am Main Teaching degree in computer science / history and bachelor's degree in computer science Professional career: 2012 today: Infomotion GmbH Consultant Focus on consulting: Data modeling ETL JAVA software development DV and Specialist conception Informatica Power Center Pentaho Data Integrator (PDI) Business Objects XII Oracle 10g / 11g Microsoft SQL Server R

6 Infomotion GmbH Specialized in Business Intelligence 7 branches with headquarters in Frankfurt 9 years of steady growth (16 million) 150+ employees and <5 freelancers 180+ customers from many industries Complete service portfolio Partnerships with leading providers Own product portfolio

7 Service portfolio Optimization and alignment of all initiatives to create an optimal basis for decision-making for the entire company. Strategy consulting Processes, key figures and KPIs for defined company areas Specialist consulting Development of solution scenarios and specialist and data processing concepts Architecture and design Implementation of the technical solution & introduction of the defined processes Implementation of customer-oriented premium operation and adaptation of BI solutions Operation Support for internal employees by experienced BI -Coach Coaching Qualification of your employees in BI technologies and methods. Training

8 Extract from the customer list Automobile Banks Chemicals, Pharmaceuticals Energy Trade KAG Consumer goods industry Mechanical engineering Transport, logistics Insurance Others. Media, Services Telecomm. Otherwise. Industries

9 Reporting to data management Holistic and user-centered provision of information Standard reporting Independent analysis of causes and relationships Ad-hoc rep. And analysis KPIs, key figures and other information at a glance Dashboards Planning and consolidation for optimal corporate management Performance management Decision-making information Filter and analyze Predictive analytics / Mining Mobile BI, Geo Intelligence, Social Intelligence, Big Data, Collaboration Current BI trends Depiction of a comprehensive and integrated approach to the management of all relevant information at company level. Enterprise Data Management Extended Information Usage Big Data Management

10 partnerships with leading providers BusinessObjects, Business Planning and Consolidation, BW, HANA, SAP Cognos BI, Cognos TM1, Cognos Express, Infosphere Warehouse, SPSS IBM Oracle BI, PL / SQL, Oracle Warehouse Builder, ODI Oracle PowerCenter, Data Quality, Test Data and Metadata Management Informatica SQL Server, Integration Services, Reporting Services, Analysis Services Microsoft SAS, QlikView, talend, Roambi, NOAD, Keyrus, DSPanel Other best practices based on many years of product experience and early evaluation of new product versions Service portfolio for special BI software products

11 Section II BI TRENDS

12 WHAT IS BUSINESS INTELLIGENCE The term Business Intelligence, abbreviation BI, became popular from the beginning to the mid-1990s and describes procedures and processes for the systematic analysis (collection, evaluation and presentation) of data in electronic form. Objectives: - better operational or strategic decisions - make business processes as well as customer and supplier relationships more profitable - lower costs - minimize risks - increase added value Source: / Access: INFOMOTION GmbH

13 BUSINESS INTELLIGENCE IN PRACTICE First task - Creation of a database on various operational systems and other sources (Data Warehouse [DWH]) Objective: - Automation of controlling, reporting, planning and forecasting - Market and customer analysis - The situation of your own company should be analyzed and, if necessary, evaluated Second task - to set up the analytical evaluations required for reporting - data and text mining mechanisms should be established - aggregation of fine-grained information to key figures - provision of data for third-party systems INFOMOTION GmbH

14 Infomotion GmbH

15 topics and trends currently being discussed Predictive Analytics Cloud BI Big Data Data Driven Agile BI / Self Service BI Visual Business Intelligence Analytical Databases Logical Data Warehouse Enterprise Data Hub Mobile BI, Geo Intelligence Infomotion GmbH


17 Evolution of BI and Analytics Infomotion GmbH

18 Analytical functions require different interventions in order to carry out actions Analysis Descriptive What happened? Human Input Diagnostic Why did it happen? Data Decision Action Predictive What will happen? Prescriptive What should I do? Decision Support Decision Automation Infomotion GmbH

19 Data Analytical maturity level Hybrid, integrated Unstructured, external Increase the analytical maturity level through: Analyzing new data sources Faster application of analytics to more decisions Expanding the portfolio to several possible uses Pervasive, real-time, embedded analytics Structured, internal, siloed Ad hoc, batch, offline analytics Descriptive Diagnostic Predictive Prescriptive Infomotion GmbH

20 CLOUD BI Infomotion GmbH

21 Cloud BI as a trend? Not today, but we plan to deploy through a public cloud in the next 12 months 1% Not today, but we plan to deploy through a hybrid public / private cloud in the next 12 months 4% Not today, but we plan to deploy through a private cloud in the next 12 months 8% Yes, through public / private cloud 4% No, we do not have or plan to deploy our BI applications in the cloud 54% Yes, through public cloud 9% Yes, through private cloud 20 % 46% of customers surveyed use cloud BI or plan to in the next 12 months (up from 30% for the past 5 years) Source: Magic Quadrant for BI and Analytics Platforms 2014 n = 1, Infomotion GmbH

22 Strategic Planning Assumption (Gartner) By 2016, 25% of net-new business analytics deployments will be in the form of subscription to cloud analytics platforms or application services. By 2016, more than 5% of the total BI, analytics and performance management market is to be driven by cloud. Infomotion GmbH

23 Cloud BI Supplier Data On-premise BI Personal Data Supply Chain Supply Chain Customer Data Cloud BI If all data is in the company, BI always tends to be in the company. The more data sources migrate to the cloud, the faster BI will also be operated in the cloud. In the future, hybrid approaches will be established more frequently, as each location has its advantage. On-premise BI Cloud BI Hybrid BI Deployments Infomotion GmbH

24 Distribution scenarios On-premise and cloud On-premise BI Cloud SaaS BA DI Platform Internal Data On-premise Cloud Data On-premise / BA in the Cloud SaaS BI DI Platform External Data IAAS On-premise Cloud Hybrid On-premises and Cloud BA SaaS DI Platform DI Platform DI Platform DI Platform Internal Data External Data IaaS Internal Data External Data IaaS On-premise Cloud On-premise Cloud Infomotion GmbH


26 Data growth requires new approaches up to now Feeding data to processing in the future Feeding processing to data Processing Processing of data Data processing of data Data Use process-centered companies: Mostly structured data Only internal data Only important data Processing of data Information-centered companies use ALL data: Multi-structured, internal & external data of any type processing relative size and complexity Infomotion GmbH

27 BIG DATA Infomotion GmbH

28 Big data comes from machines GPS, RFID, hypervisor, web servers, messaging, clickstreams, mobile, telephony, IVR, databases, sensors, telematics, storage, servers, security devices, desktops Infomotion GmbH

29 Definition of Big Data Amounts of data (volume) Number of data records and files Yottabytes Zettabytes Exabytes Petabytes Terabytes Data generation at high speed Transmission of constantly generated data Real-time Milliseconds Seconds I Minutes I Hours Speed ​​(Velocity) Big Data Variety of data (Web etc.) Company data Unstructured, semi-structured, structured data Presentations I Texts I Images I Tweets I Blogs Communication between machines Recognition of connections, meanings, patterns Predictive models Data mining Text mining Image analysis I Visualization I Realtime analytics Source: Management of Big Data Projects Guide, Bitcom 2013, p Infomotion GmbH

30 Classic BI technology stack Decision-making information Filter and analyze data Data Mining & Analytics Provision of processed, aggregated and filtered information Data warehouse Independent analysis of causes and relationships Ad-hoc rep. And analysis Holistic and user-centered provision of information Standard reporting KPIs, key figures and other information at a glance Dashboards In this step, the data ultimately required for reporting are retrieved from the source systems, processed and loaded into the DWH. Extract Transform Load Retrieve and sort out required information Filter Prepare & enrich information Processing Transfer information to the DWH in a targeted manner Loading The source data is highly structured and available for retrieval in internal company databases. Structured internal data Marketing Sales Infomotion GmbH

31 Business Intelligence with Big Data Technology With this layer, the sometimes high latency of the storage layer is compensated and information is made available in a target system-specific manner. Server layer Information storage target system 1 Information storage target system 1I Use case specific information & reporting systems Target systems KPIs, key figures and other information at a glance in real time Real-time dashboards In this layer (raw) data is stored and processed in batch mode. The preparation takes place specifically for various decreasing information storage for systems. Raw data Batch processing & storage layer Data hub processing target system-specific processing Specific batch processing Transferring information to specific information storage systems Loading This layer is responsible for transport, filtering and processing in almost real time. Transport layer Information push shortly after occurrence Store raw data in the data hub near real-time Loading Filtering, analysis, processing & forwarding in the stream for certain target systems Livestream data processing The source data is poly-structured in databases that are available both internally and externally. Polystructured data Internal DBs Weather Movement Products Log data Social Media Infomotion GmbH


33 Career entry Studies Lecture Infomotion Internship Final thesis Hiring as a consultant

34 Opportunities for cooperation Internship Final thesis Working student position Entry into consulting

35 Contact for applications You can address questions and applications to our contact person! ANNA-LENA BURK Graduated Economist Human Resources Officer INFOMOTION GMBH LUDWIGSTRASSE FRANKFURT T: +49 (0) F: +49 (0)

36 Your questions SEBASTIAN SCHADE Diploma Business Information Technology Professional Consultant INFOMOTION GMBH LUDWIGSTRASSE FRANKFURT AM MAIN T: +49 (0) F: +49 (0) TIM KRETZSCHMAR Consultant INFOMOTION GMBH LUDWIGSTRASSE FRANKFURT AM MAIN T: +49 (0) F: +49 ( 0)