Bull Fast Track/PDW and Big Data

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Julia Clark
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1 Bull Fast Track/PDW and Big Data Add High Performance BI to your Big Data Roger Van Unen Expert Microsoft / BI roger.van-unen@bull.net Michael Schmitter BI Sales Germany m.schmitter@bull.de page: 1

2 Agenda 1. What is BI and how is it changed 2. Relational vs. non-relational 3. Structured vs. unstructured data 4. What is Big Data and how do you get it? 5. BIG DATA is all about the 4 V s 6. A closer look at: Web Site Logging, Twitter, Facebook and DWH logging 7. Hadoop (non-relational) vs. relational systems 8. Why not Hadoop WITH a relational system? 9. Why from Big Data to Bull Fast Track or PDW appliance? 10. Bull PDW appliance 11. Existing customer cases and future possibilities 12. What could be in the Fast Track / PDW appliance 13. Bull Fast Track Appliances for Proof Of Concept page: 2

3 What is BI or Business Intelligence? Spending data Financial data Logistics data Financial Data Mart D D D Sales Data Mart D HR Data Mart Customer data HR data F D Service data Marketing data Enterprise Data Warehouse Sales data F a s t Tr a c k Marketing Data Mart D D Service Data Mart Customer Data Mart?? EXTERNAL DATA?? page: 3

Evolution of Business Intelligence Traditional Business Intelligence

Reporting Dashboards & Scorecards Users Extract, transform,

Data Warehouse Specialised applications Excel sheets Existing

department How to The take to IT extract department be control

transform and it they right reports still pressure have deliver but

users it and way results requested better to load much now solution?

4 Evolution of Business Intelligence Traditional Business Intelligence BI in Self-Service Visualise and exploit the information Analysis Reporting Dashboards & Scorecards Users Extract, transform, consolidate, improve the quality and load the data Analysis Cubes Data Warehouse Specialised applications Excel sheets Existing sources Mission critical applications Data Marts Files The IT users department How to The take to IT extract department be control finally more wants the create because data, agile to is do under the transform and it they right reports still pressure have deliver but and that that to clean a to the deliver takes maintainable perform users it and way results requested better to load much now solution? in it and BI time not for in the 3 business who needs to react to the market IT Pro months page: 4

Business Intelligence on Self service BI BI made available for sharing Visualise and exploit the information in Excel with PowerPivot Analysis Reporting Dashboards & Scorecards IT Pro Extract,

) Deliver at IT Excel sheets with Power Pivot (+ Power View in 2013) External files (Excel, CSV, etc.

5 Business Intelligence on Self service BI BI made available for sharing Visualise and exploit the information in Excel with PowerPivot Analysis Reporting Dashboards & Scorecards IT Pro Extract, transform, consolidate, improve the quality of the data with DAX Excel sheets with Power Pivot (+ Power View in 2013) External files (Excel, CSV, etc.) Deliver at IT Excel sheets with Power Pivot (+ Power View in 2013) External files (Excel, CSV, etc.) Existing sources made available by IT Mission critical applications Data Marts Data Warehouse Industrialized connections Tabular Cubes Restore the PowerPivot cube, industrialize connections, rights and processing Users Users Users Users The IT And restores users The IT when department users The create it the users into work interactive PowerPivot a discuss gives tabular on the direct data, cube, with dashboards access IT enrich optimise is the finalized resources to it and with the and reports users external they industrialize they hand or on need. delivers data the it over pivot the files to cube table IT page: 5

6 page: 6

7 Relational vs. Non-Relational page: 7

8 Big Data is all about the 4 V s Big Data is all about Volume, Velocity, Variability and Variety page: 8

9 What is Big Data and how do you get it? Web farm HA transaction database servers Internet Logging Hadoop database servers servers NLB page: 9

10 Structured vs. unstructured data relational Non-relational page: 10

11 A closer look at web site logging Then skip lines to get the next relevant information page: 11

12 A closer look at Twitter Let s search for SQL Server 2012: Formatting this in our favourite formatting tool, Notepad we get: But what we want is actually searching in data like this: page: 12

13 A closer look at Facebook page: 13

14 Historization of ERP into DWH Financial Data Mart Enterprise Data Warehouse Enterprise Data Warehouse Marketing Data Mart Customer Data Mart page: 14

15 Hadoop (non-relational) vs. relational systems page: 15

16 Why not Hadoop WITH a relational system? page: 16

17 Why from Big Data to Bull Fast Track or PDW? bull fast track 40 bull fast track 12 bull fast track 16 bull fast track 24 bull fast track 40 bull fast track 48 bull fast track 80 page: 17

Capacity Start small with a few Terabyte warehouse Add capacity up to 5

18 Bull PDW appliance Smallest (0TB) To Largest (5PB) Add Capacity Massively multiprocessing (MPP) instead of symmetric multiprocessing (SMP) Add Capacity Start small with a few Terabyte warehouse Add capacity up to 5 Petabytes 0TB 5 PB Start Small And Grow Largest Warehouse PB No Downtime page: 18

Bull PDW appliance advantage SQL Single Query;

tables with Relational Tables SQL Server 2012 PDW

From Where Database HDFS (Hadoop) Existing SQL

19 Bull PDW appliance advantage SQL Single Query; Structured and Unstructured Query and join Hadoop tables with Relational Tables SQL Server 2012 PDW Powered by PolyBase Use Standard SQL language Select, From Where Database HDFS (Hadoop) Existing SQL Skillset No IT Intervention Save Time and Costs Analyze All Data Types page: 19

20 Customer cases: AT Internet web site clicks page: 20

21 Customer cases: L Oreal DWH too small page: 21

22 Fast Track customer case POC page: 22

What could be in the Fast Track / PDW appliance

development tools Data Tools BIG DATA HADOOP Cluster

Services Master Data Management Bull Fast Track or

OLAP Cubes Tabular Cubes Data mining Excel

23 What could be in the Fast Track / PDW appliance Advanced administration Management Studio and development tools Data Tools BIG DATA HADOOP Cluster SQL Server Data Quality Services Manage your Data Quality SQL Server Integration Services Extract/Transform/Load (ETL) SQL Server Master Data Services Master Data Management Bull Fast Track or Bull PDW Data Warehouse SQL Server Analysis Services OLAP Cubes Tabular Cubes Data mining Excel PowerPivot Power View SharePoint BI Dashboards SQL Server Reporting Services page: 23

24 page: 24

The Bull Fast Track Appliance at MTC for POC SQL Server Data Quality Services SQL Server Master Data Services SQL Server Tabular Cubes SQL Server

25 The Bull Fast Track Appliance at MTC for POC SQL Server Data Quality Services SQL Server Master Data Services SQL Server Tabular Cubes SQL Server Integration Services SharePoint 2010 BI Portal SQL Server PowerPivot SQL Server Reporting Services SQL Server Data Warehouse SQL Server Power View page: 25

26 Bull DBUS offer page: 28

27 Decide but fast page: 29

28 Thank you page: 30

Přehled novinek v SQL Server 2016

Přehled novinek v SQL Server 2016 Martin Rys, BI Competency Leader martin.rys@adastragrp.com https://www.linkedin.com/in/martinrys 20.4.2016 1 BI Competency development 2 Trends, modern data warehousing