Microsoft Developer Day
|
|
- Sharlene Hancock
- 5 years ago
- Views:
Transcription
1 Microsoft Developer Day
2 Pradeep Menon Microsoft Developer Day Solutions Architect
3 Agenda Microsoft Developer Day
4 Traditional Business Intelligence Architecture Structured Sources Extract Transform Structurize Load Enterprise Warehouse marts Reports OLAP Key Notes: Philosophy: Understand data. Transform data. Load data. Analyze data. More time spent on ETL. Less time for spend on analysis. discovery is a challenge. Not all data is analyzed.
5 in the Era of Big 1 in 3 leaders don t trust their data 100 TB of data per US company quality costs $600B/year 200 billion photos 600 years of videos Veracity Variety Big Volume Velocity 6 Billion smart phones 1PB of created every year Upto 100 sensors in modern car 0 million tweets/day 20 million n/w connections by 2020 The definition of analyzable data has changed. Traditional sources of data is disrupted.
6 Processing, Storage and Cost Moore s Law Processing capability has increased 10,000 times since 2000 Cost of storage has reduced by 1000 times since 2000 Capability to analyze more data efficiently 1 TB blob storage = $24/month
7 Lake Concept Lake Warehouse/Mart
8 Conceptual Lake Architecture Discovery Exploratory Analysis Predictive Modeling Structured Sources EL Raw Store Batch- Processing Engine Processed Stores Reports Unstructured Sources EL Real-Time Processing Engine Cataloging and Curation Security and Governance
9 Key Component Groups - Lambda Batch layer Structured Sources Unstructured Sources EL Lambda Architecture EL Raw Store Batch- Processing Engine Real-Time Processing Engine Speed layer Processed Stores Process: Batch Layer stores all the data in the rawest form possible, this set is the master data set. The master data set is immutable. follows a fact-based model, where each piece is atomic and timestamped. Streaming data follows both path. The speed layer allows random writes and the result are transient. Caters to both data on rest and data in motion
10 Key Component Groups- Analytical Sandboxes Discovery Exploratory Analysis Raw Store Analytical Sandboxes Predictive Modeling Batch- Processing Engine Processed Stores Process: Develop and test hypothesis. Explore data. Rapid prototyping. Discover data. Generate use-cases. Discover data. Extract value. Transform business
11 30 Key Component Groups Catalog and Governance Discovery Cataloging and Governance Exploratory Analysis Predictive Modeling How much does this painting cost? Structured Sources Unstructured Sources EL EL Raw Store Batch- Processing Engine Real-Time Processing Engine Processed Stores Cataloging and Curation Security and Governance Reports Catalog Information: The Old Guitarist Pablo Picasso 1903 Est: Over $100 million cataloging and curation is the key to extract value from data.
12 Key Component Groups Catalog Map Business Term Definition Logical Models Logical Entities More.. Business Term base Physical Model Tables Columns Primary keys Quality Score Schemas Lineage Information Class More.. Business Metadata Technical Metadata
13 EL Discovery EL Raw Store Exploratory Analysis Predictive Modeling Batch- Processing Engine Real-Time Processing Engine Processed Stores Cataloging and Curation Security and Governance Reports Difference between Lake and EDW Structured Sources Structured Sources Extract Transform Structurize Load Enterprise Warehouse marts Reports OLAP Unstructured Sources Lake Philosophy: Load first. Understand later. Retains all data i.e. stores data in its raw form. Supports all kinds of data Supports all kinds of users Adapts to change easily as requirements evolve Provides active cataloging of raw and transformed data Warehouse Philosophy: Understand first. Load later. Refined and transformed data structure for specific business requirement Optimized only for structured data stores Targeted to support operational users Relatively difficult to change as the data is highly structurized Provides limited metadata capture features
14 Azure Services for Lake Architecture Machine Learning Discovery Exploratory Analysis Predictive Modeling SSIS Factory EL Raw Store HDInsight Factory SSIS Batch- Processing Engine Processed Stores Reports Storage blob Lake Azure SQL database Stream Analytics Event Hubs Real-Time Processing Engine SQL Warehouse DocumentDB Cataloging and Curation Security and Governance Azure Access Active DirectoryControl
15 Key Takeaways 1. Lakes is a new paradigm shift for Big Architecture. 2. Lakes caters to all kinds of data, stores data in the raw form, caters to spectrum of users and enables faster insights. 3. Meticulous data cataloging and governance is key for successful data lake implementation. 4. Azure offers end-end solution for implementation of data lake architecture in an economical and scalable way.
16
17 Demo Architecture - Lambda Storage blob Event Hubs Stream Analytics
18 Demo Architecture Catalog Wine Quality Adventure Works Storage blob On-Prem SQL DB Cataloging and Curation
19 References Related references for you to expand your knowledge on the subject Azure Portal Azure Updates Microsoft Virtual Academy aka.ms/mva Developer Network msdn.microsoft.com/
20 Thank you Follow us online Microsoft Developer Day
21 Tell us what you think Help us shape future events by sharing your valuable feedback. Link - #MSDevDay
Modern Data Warehouse The New Approach to Azure BI
Modern Data Warehouse The New Approach to Azure BI History On-Premise SQL Server Big Data Solutions Technical Barriers Modern Analytics Platform On-Premise SQL Server Big Data Solutions Modern Analytics
More informationOliver Engels & Tillmann Eitelberg. Big Data! Big Quality?
Oliver Engels & Tillmann Eitelberg Big Data! Big Quality? Like to visit Germany? PASS Camp 2017 Main Camp 5.12 7.12.2017 (4.12 Kick Off Evening) Lufthansa Training & Conference Center, Seeheim SQL Konferenz
More informationAzure Data Factory VS. SSIS. Reza Rad, Consultant, RADACAD
Azure Data Factory VS. SSIS Reza Rad, Consultant, RADACAD 2 Please silence cell phones Explore Everything PASS Has to Offer FREE ONLINE WEBINAR EVENTS FREE 1-DAY LOCAL TRAINING EVENTS VOLUNTEERING OPPORTUNITIES
More informationData Architectures in Azure for Analytics & Big Data
Data Architectures in for Analytics & Big Data October 20, 2018 Melissa Coates Solution Architect, BlueGranite Microsoft Data Platform MVP Blog: www.sqlchick.com Twitter: @sqlchick Data Architecture A
More informationOliver Engels & Tillmann Eitelberg. Big Data! Big Quality?
Oliver Engels & Tillmann Eitelberg Big Data! Big Quality? Sponsors help us to run this event! THX! You Rock! Sponsor Gold Sponsor Silver Sponsor Bronze Sponsor You Rock! Sponsor Session 13:45 Track 1 Das
More informationData sources. Gartner, The State of Data Warehousing in 2012
data warehousing has reached the most significant tipping point since its inception. The biggest, possibly most elaborate data management system in IT is changing. Gartner, The State of Data Warehousing
More informationBest practices for building a Hadoop Data Lake Solution CHARLOTTE HADOOP USER GROUP
Best practices for building a Hadoop Data Lake Solution CHARLOTTE HADOOP USER GROUP 07.29.2015 LANDING STAGING DW Let s start with something basic Is Data Lake a new concept? What is the closest we can
More informationOverview of Data Services and Streaming Data Solution with Azure
Overview of Data Services and Streaming Data Solution with Azure Tara Mason Senior Consultant tmason@impactmakers.com Platform as a Service Offerings SQL Server On Premises vs. Azure SQL Server SQL Server
More informationProcessing Unstructured Data. Dinesh Priyankara Founder/Principal Architect dinesql Pvt Ltd.
Processing Unstructured Data Dinesh Priyankara Founder/Principal Architect dinesql Pvt Ltd. http://dinesql.com / Dinesh Priyankara @dinesh_priya Founder/Principal Architect dinesql Pvt Ltd. Microsoft Most
More informationSwimming in the Data Lake. Presented by Warner Chaves Moderated by Sander Stad
Swimming in the Data Lake Presented by Warner Chaves Moderated by Sander Stad Thank You microsoft.com hortonworks.com aws.amazon.com red-gate.com Empower users with new insights through familiar tools
More informationData Management Glossary
Data Management Glossary A Access path: The route through a system by which data is found, accessed and retrieved Agile methodology: An approach to software development which takes incremental, iterative
More informationWhite Paper / Azure Data Platform: Ingest
White Paper / Azure Data Platform: Ingest Contents White Paper / Azure Data Platform: Ingest... 1 Versioning... 2 Meta Data... 2 Foreword... 3 Prerequisites... 3 Azure Data Platform... 4 Flowchart Guidance...
More informationData sources. Gartner, The State of Data Warehousing in 2012
data warehousing has reached the most significant tipping point since its inception. The biggest, possibly most elaborate data management system in IT is changing. Gartner, The State of Data Warehousing
More informationFrom Single Purpose to Multi Purpose Data Lakes. Thomas Niewel Technical Sales Director DACH Denodo Technologies March, 2019
From Single Purpose to Multi Purpose Data Lakes Thomas Niewel Technical Sales Director DACH Denodo Technologies March, 2019 Agenda Data Lakes Multiple Purpose Data Lakes Customer Example Demo Takeaways
More information##SQLSatMadrid. Project [Vélib by Cortana]
Project [Vélib by Cortana] BIG Thanks to SQLSatMadrid Sponsors Speakers Agenda Presentation of the Project Cortana Intelligent Suite Creation of the architecture Purpose of the Project Get a descriptive
More information@Pentaho #BigDataWebSeries
Enterprise Data Warehouse Optimization with Hadoop Big Data @Pentaho #BigDataWebSeries Your Hosts Today Dave Henry SVP Enterprise Solutions Davy Nys VP EMEA & APAC 2 Source/copyright: The Human Face of
More informationDesigning a Modern Data Warehouse + Data Lake
Designing a Modern Warehouse + Lake Strategies & architecture options for implementing a modern data warehousing environment Melissa Coates Analytics Architect, SentryOne Blog: sqlchick.com Twitter: @sqlchick
More informationBig Data Technology Ecosystem. Mark Burnette Pentaho Director Sales Engineering, Hitachi Vantara
Big Data Technology Ecosystem Mark Burnette Pentaho Director Sales Engineering, Hitachi Vantara Agenda End-to-End Data Delivery Platform Ecosystem of Data Technologies Mapping an End-to-End Solution Case
More informationTake P, R or U. and solve your data quality problems Oliver Engels & Tillmann Eitelberg, OH22
Take P, R or U and solve your data quality problems Oliver Engels & Tillmann Eitelberg, OH22 Oliver Engels CEO, oh22data AG @oengels Datamonster from Germany MS Data Platform MVP President of PASS Germany
More informationThink & Work like a Data Scientist with SQL 2016 & R DR. SUBRAMANI PARAMASIVAM (MANI)
Think & Work like a Data Scientist with SQL 2016 & R DR. SUBRAMANI PARAMASIVAM (MANI) About the Speaker Dr. SubraMANI Paramasivam PhD., MCT, MCSE, MCITP, MCP, MCTS, MCSA CEO, Principal Consultant & Trainer
More informationWhat is Data Warehouse like
What is Data Warehouse like in the Big Data Era? Sales (Asia) Data Warehouse Sales (US) ETL ETL Collects and organizes historical data from multiple sources Inventory Advertising ETL ETL So far Ø Star
More informationAlexander Klein. #SQLSatDenmark. ETL meets Azure
Alexander Klein ETL meets Azure BIG Thanks to SQLSat Denmark sponsors Save the date for exiting upcoming events PASS Camp 2017 Main Camp 05.12. 07.12.2017 (04.12. Kick-Off abends) Lufthansa Training &
More informationThe Emerging Data Lake IT Strategy
The Emerging Data Lake IT Strategy An Evolving Approach for Dealing with Big Data & Changing Environments bit.ly/datalake SPEAKERS: Thomas Kelly, Practice Director Cognizant Technology Solutions Sean Martin,
More informationModernizing Business Intelligence and Analytics
Modernizing Business Intelligence and Analytics Justin Erickson Senior Director, Product Management 1 Agenda What benefits can I achieve from modernizing my analytic DB? When and how do I migrate from
More informationDr. SubraMANI Paramasivam. Think & Work like a Data Scientist with SQL 2016 & R
Dr. SubraMANI Paramasivam Think & Work like a Data Scientist with SQL 2016 & R About the Speaker Group Leader Dr. SubraMANI Paramasivam PhD., MVP, MCT, MCSE (x2), MCITP (x2), MCP, MCTS (x3), MCSA CEO,
More informationAsanka Padmakumara. ETL 2.0: Data Engineering with Azure Databricks
Asanka Padmakumara ETL 2.0: Data Engineering with Azure Databricks Who am I? Asanka Padmakumara Business Intelligence Consultant, More than 8 years in BI and Data Warehousing A regular speaker in data
More informationData 101 Which DB, When. Joe Yong Azure SQL Data Warehouse, Program Management Microsoft Corp.
Data 101 Which DB, When Joe Yong (joeyong@microsoft.com) Azure SQL Data Warehouse, Program Management Microsoft Corp. The world is changing AI increased by 300% in 2017 Data will grow to 44 ZB in 2020
More informationCapture Business Opportunities from Systems of Record and Systems of Innovation
Capture Business Opportunities from Systems of Record and Systems of Innovation Amit Satoor, SAP March Hartz, SAP PUBLIC Big Data transformation powers digital innovation system Relevant nuggets of information
More informationMAPR DATA GOVERNANCE WITHOUT COMPROMISE
MAPR TECHNOLOGIES, INC. WHITE PAPER JANUARY 2018 MAPR DATA GOVERNANCE TABLE OF CONTENTS EXECUTIVE SUMMARY 3 BACKGROUND 4 MAPR DATA GOVERNANCE 5 CONCLUSION 7 EXECUTIVE SUMMARY The MapR DataOps Governance
More informationCloudSwyft Learning-as-a-Service Course Catalog 2018 (Individual LaaS Course Catalog List)
CloudSwyft Learning-as-a-Service Course Catalog 2018 (Individual LaaS Course Catalog List) Microsoft Solution Latest Sl Area Refresh No. Course ID Run ID Course Name Mapping Date 1 AZURE202x 2 Microsoft
More informationWHITE PAPER: TOP 10 CAPABILITIES TO LOOK FOR IN A DATA CATALOG
WHITE PAPER: TOP 10 CAPABILITIES TO LOOK FOR IN A DATA CATALOG The #1 Challenge in Successfully Deploying a Data Catalog The data cataloging space is relatively new. As a result, many organizations don
More informationOracle Big Data Discovery
Oracle Big Data Discovery Turning Data into Business Value Harald Erb Oracle Business Analytics & Big Data 1 Safe Harbor Statement The following is intended to outline our general product direction. It
More informationStages of Data Processing
Data processing can be understood as the conversion of raw data into a meaningful and desired form. Basically, producing information that can be understood by the end user. So then, the question arises,
More informationCONSOLIDATING RISK MANAGEMENT AND REGULATORY COMPLIANCE APPLICATIONS USING A UNIFIED DATA PLATFORM
CONSOLIDATING RISK MANAGEMENT AND REGULATORY COMPLIANCE APPLICATIONS USING A UNIFIED PLATFORM Executive Summary Financial institutions have implemented and continue to implement many disparate applications
More informationMicrosoft Azure Databricks for data engineering. Building production data pipelines with Apache Spark in the cloud
Microsoft Azure Databricks for data engineering Building production data pipelines with Apache Spark in the cloud Azure Databricks As companies continue to set their sights on making data-driven decisions
More informationHow Insurers are Realising the Promise of Big Data
How Insurers are Realising the Promise of Big Data Jason Hunter, CTO Asia-Pacific, MarkLogic A Big Data Challenge: Pushing the Limits of What's Possible The Art of the Possible Multiple Government Agencies
More informationProcessing Big Data. with AZURE DATA LAKE ANALYTICS. Sean Forgatch - Senior Consultant. 6/23/ TALAVANT. All Rights Reserved.
Processing Big Data with AZURE DATA LAKE ANALYTICS Sean Forgatch - Senior Consultant 6/23/2018 2018 TALAVANT. All Rights Reserved. 1 SQL Saturday Iowa 2018 6/23/2018 2018 TALAVANT. All Rights Reserved.
More informationCortana Intelligence Suite; Where the Magic Happens
Cortana Intelligence Suite; Where the Magic Happens Reza Rad, Leila Etaati #509 Brisbane 2016 About Us Reza Rad Leila Etaati MVP BI Consultant and Trainer Author of Books Speaker in conferences; PASS Summit,
More informationData Warehouse Design Decisions
Data Warehouse Design Decisions August 2015 Colleen Barnitz Director, IT Development MVT Services Colleen Barnitz over 20 Years in IT worked with SQL Server since version 6.5 developer and an architect
More informationBuild an open hybrid cloud and paint it red and blue
Build an open hybrid cloud and paint it red and blue Khaled Elbedri Technical sales lead, Microsoft Ismail Dhaoui EMEA Senior Specialist Solutions Architect, Red Hat Tuesday, May 8, 2018 Agenda RH & MS
More informationTaming Structured And Unstructured Data With SAP HANA Running On VCE Vblock Systems
1 Taming Structured And Unstructured Data With SAP HANA Running On VCE Vblock Systems The Defacto Choice For Convergence 2 ABSTRACT & SPEAKER BIO Dealing with enormous data growth is a key challenge for
More informationMigrating Enterprise BI to Azure
Migrating Enterprise BI to Azure Best Practices Wlodek Bielski SQLSat Kyiv Team Yevhen Nedashkivskyi Mykola Pobyivovk Denis Reznik Eugene Polonichko Oksana Borysenko Oksana Tkach Sponsors Session will
More informationWhat is Gluent? The Gluent Data Platform
What is Gluent? The Gluent Data Platform The Gluent Data Platform provides a transparent data virtualization layer between traditional databases and modern data storage platforms, such as Hadoop, in the
More informationIOTA ARCHITECTURE: DATA VIRTUALIZATION AND PROCESSING MEDIUM DR. KONSTANTIN BOUDNIK DR. ALEXANDRE BOUDNIK
IOTA ARCHITECTURE: DATA VIRTUALIZATION AND PROCESSING MEDIUM DR. KONSTANTIN BOUDNIK DR. ALEXANDRE BOUDNIK DR. KONSTANTIN BOUDNIK DR.KONSTANTIN BOUDNIK EPAM SYSTEMS CHIEF TECHNOLOGIST BIGDATA, OPEN SOURCE
More informationSQL Server 2017 Power your entire data estate from on-premises to cloud
SQL Server 2017 Power your entire data estate from on-premises to cloud PREMIER SPONSOR GOLD SPONSORS SILVER SPONSORS BRONZE SPONSORS SUPPORTERS Vulnerabilities (2010-2016) Power your entire data estate
More informationIntegrating Oracle Databases with NoSQL Databases for Linux on IBM LinuxONE and z System Servers
Oracle zsig Conference IBM LinuxONE and z System Servers Integrating Oracle Databases with NoSQL Databases for Linux on IBM LinuxONE and z System Servers Sam Amsavelu Oracle on z Architect IBM Washington
More informationHDInsight > Hadoop. October 12, 2017
HDInsight > Hadoop October 12, 2017 2 Introduction Mark Hudson >20 years mixing technology with data >10 years with CapTech Microsoft Certified IT Professional Business Intelligence Member of the Richmond
More informationCOURSE 20466D: IMPLEMENTING DATA MODELS AND REPORTS WITH MICROSOFT SQL SERVER
ABOUT THIS COURSE The focus of this five-day instructor-led course is on creating managed enterprise BI solutions. It describes how to implement multidimensional and tabular data models, deliver reports
More informationThe Cortana Intelligence Suite
Slide 1 The Cortana Intelligence Suite Foundations Data Discovery and Ingestion Microsoft Machine Learning and Data Science Team CortanaIntelligence.com Main page: http://cortanaanalytics.com To begin
More informationVirtuoso Infotech Pvt. Ltd.
Virtuoso Infotech Pvt. Ltd. About Virtuoso Infotech Fastest growing IT firm; Offers the flexibility of a small firm and robustness of over 30 years experience collectively within the leadership team Technology
More informationBigInsights and Cognos Stefan Hubertus, Principal Solution Specialist Cognos Wilfried Hoge, IT Architect Big Data IBM Corporation
BigInsights and Cognos Stefan Hubertus, Principal Solution Specialist Cognos Wilfried Hoge, IT Architect Big Data 2013 IBM Corporation A Big Data architecture evolves from a traditional BI architecture
More informationGabriel Villa. Architecting an Analytics Solution on AWS
Gabriel Villa Architecting an Analytics Solution on AWS Cloud and Data Architect Skilled leader, solution architect, and technical expert focusing primarily on Microsoft technologies and AWS. Passionate
More informationexam. Microsoft Perform Data Engineering on Microsoft Azure HDInsight. Version 1.0
70-775.exam Number: 70-775 Passing Score: 800 Time Limit: 120 min File Version: 1.0 Microsoft 70-775 Perform Data Engineering on Microsoft Azure HDInsight Version 1.0 Exam A QUESTION 1 You use YARN to
More informationOskari Heikkinen. New capabilities of Azure Data Factory v2
Oskari Heikkinen New capabilities of Azure Data Factory v2 Oskari Heikkinen Lead Cloud Architect at BIGDATAPUMP Microsoft P-TSP Azure Advisors Numerous projects on Azure Worked with Microsoft Data Platform
More informationDrawing the Big Picture
Drawing the Big Picture Multi-Platform Data Architectures, Queries, and Analytics Philip Russom TDWI Research Director for Data Management August 26, 2015 Sponsor 2 Speakers Philip Russom TDWI Research
More informationThe Data Catalog The Key to Managing Data, Big and Small. April Reeve May
The Data Catalog The Key to Managing Data, Big and Small April Reeve May 18 2017 April Reeve Thirty years doing data oriented stuff Data Management disciplines Data Integration, Data Governance, Data Modeling,
More informationAzure Data Lake Store
Azure Data Lake Store Analytics 101 Kenneth M. Nielsen Data Solution Architect, MIcrosoft Our Sponsors About me Kenneth M. Nielsen Worked with SQL Server since 1999 Data Solution Architect at Microsoft
More informationData Lakes. IN A Modern Data Architecture
Data Lakes IN A Modern Data Architecture Data is Big Space is big, Douglas Adams mused in The Hitchhiker s Guide to the Galaxy. Really big. The same can be said of data: It s big. Really big. You might
More informationIBM Data Replication for Big Data
IBM Data Replication for Big Data Highlights Stream changes in realtime in Hadoop or Kafka data lakes or hubs Provide agility to data in data warehouses and data lakes Achieve minimum impact on source
More informationBIG DATA TESTING: A UNIFIED VIEW
http://core.ecu.edu/strg BIG DATA TESTING: A UNIFIED VIEW BY NAM THAI ECU, Computer Science Department, March 16, 2016 2/30 PRESENTATION CONTENT 1. Overview of Big Data A. 5 V s of Big Data B. Data generation
More informationBuilding Next- GeneraAon Data IntegraAon Pla1orm. George Xiong ebay Data Pla1orm Architect April 21, 2013
Building Next- GeneraAon Data IntegraAon Pla1orm George Xiong ebay Data Pla1orm Architect April 21, 2013 ebay Analytics >50 TB/day new data 100+ Subject Areas >100 PB/day Processed >100 Trillion pairs
More informationIntroduction to Data Science
UNIT I INTRODUCTION TO DATA SCIENCE Syllabus Introduction of Data Science Basic Data Analytics using R R Graphical User Interfaces Data Import and Export Attribute and Data Types Descriptive Statistics
More informationOptimizing and Modeling SAP Business Analytics for SAP HANA. Iver van de Zand, Business Analytics
Optimizing and Modeling SAP Business Analytics for SAP HANA Iver van de Zand, Business Analytics Early data warehouse projects LIMITATIONS ISSUES RAISED Data driven by acquisition, not architecture Too
More informationMicrosoft Exam
Volume: 42 Questions Case Study: 1 Relecloud General Overview Relecloud is a social media company that processes hundreds of millions of social media posts per day and sells advertisements to several hundred
More informationNPP & Blockchain Have you thought about the data? Ken Krupa, CTO, MarkLogic
NPP & Blockchain Have you thought about the data? Ken Krupa, CTO, MarkLogic Hello SLIDE: 2 14 COPYRIGHT November 2017 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED. A QUICK LOOK New Payments Platform Open
More informationTop Five Reasons for Data Warehouse Modernization Philip Russom
Top Five Reasons for Data Warehouse Modernization Philip Russom TDWI Research Director for Data Management May 28, 2014 Sponsor Speakers Philip Russom TDWI Research Director, Data Management Steve Sarsfield
More informationIndex. Scott Klein 2017 S. Klein, IoT Solutions in Microsoft s Azure IoT Suite, DOI /
Index A Advanced Message Queueing Protocol (AMQP), 44 Analytics, 9 Apache Ambari project, 209 210 API key, 244 Application data, 4 Azure Active Directory (AAD), 91, 257 Azure Blob Storage, 191 Azure data
More informationSAP Agile Data Preparation Simplify the Way You Shape Data PUBLIC
SAP Agile Data Preparation Simplify the Way You Shape Data Introduction SAP Agile Data Preparation Overview Video SAP Agile Data Preparation is a self-service data preparation application providing data
More informationHandout 12 Data Warehousing and Analytics.
Handout 12 CS-605 Spring 17 Page 1 of 6 Handout 12 Data Warehousing and Analytics. Operational (aka transactional) system a system that is used to run a business in real time, based on current data; also
More information#techsummitch
www.thomasmaurer.ch #techsummitch Justin Incarnato Justin Incarnato Microsoft Principal PM - Azure Stack Hyper-scale Hybrid Power of Azure in your datacenter Azure Stack Enterprise-proven On-premises
More informationUSERS CONFERENCE Copyright 2016 OSIsoft, LLC
Bridge IT and OT with a process data warehouse Presented by Matt Ziegler, OSIsoft Complexity Problem Complexity Drives the Need for Integrators Disparate assets or interacting one-by-one Monitoring Real-time
More informationAzure Data Factory. Data Integration in the Cloud
Azure Data Factory Data Integration in the Cloud 2018 Microsoft Corporation. All rights reserved. This document is provided "as-is." Information and views expressed in this document, including URL and
More informationBull Fast Track/PDW and Big Data
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 http://www.bull.fr/bi/fastrack.html Michael Schmitter BI Sales Germany
More information2014 年 3 月 13 日星期四. From Big Data to Big Value Infrastructure Needs and Huawei Best Practice
2014 年 3 月 13 日星期四 From Big Data to Big Value Infrastructure Needs and Huawei Best Practice Data-driven insight Making better, more informed decisions, faster Raw Data Capture Store Process Insight 1 Data
More informationTamr Technical Whitepaper
Tamr Technical Whitepaper 1. Executive Summary Tamr was founded to tackle large-scale data management challenges in organizations where extreme data volume and variety require an approach different from
More informationSQL Server SQL Server 2008 and 2008 R2. SQL Server SQL Server 2014 Currently supporting all versions July 9, 2019 July 9, 2024
Current support level End Mainstream End Extended SQL Server 2005 SQL Server 2008 and 2008 R2 SQL Server 2012 SQL Server 2005 SP4 is in extended support, which ends on April 12, 2016 SQL Server 2008 and
More informationOpen Source Tools as a platform for research on Microsoft Azure
Open Source Tools as a platform for research on Microsoft Azure Alessandro Jannuzi Open Source Lead Microsoft Brasil Jaime Puente Director Microsoft Research Azure, Microsoft Cloud Platform 24 Regions
More informationSmart Data Catalog DATASHEET
DATASHEET Smart Data Catalog There is so much data distributed across organizations that data and business professionals don t know what data is available or valuable. When it s time to create a new report
More informationBig Data - Some Words BIG DATA 8/31/2017. Introduction
BIG DATA Introduction Big Data - Some Words Connectivity Social Medias Share information Interactivity People Business Data Data mining Text mining Business Intelligence 1 What is Big Data Big Data means
More informationSolving the Enterprise Data Dilemma
Solving the Enterprise Data Dilemma Harmonizing Data Management and Data Governance to Accelerate Actionable Insights Learn More at erwin.com Is Our Company Realizing Value from Our Data? If your business
More informationmicrosoft
70-775.microsoft Number: 70-775 Passing Score: 800 Time Limit: 120 min Exam A QUESTION 1 Note: This question is part of a series of questions that present the same scenario. Each question in the series
More informationInformatica Enterprise Information Catalog
Data Sheet Informatica Enterprise Information Catalog Benefits Automatically catalog and classify all types of data across the enterprise using an AI-powered catalog Identify domains and entities with
More informationThe OLX data theory of everything
The OLX data theory of everything Caspar Schönau Head of Global BI Jakub Orłowski Data engineering manager The biggest internet company that you have never heard of Founded 1915 South-Africa Market cap:
More informationIntelligence for the connected world How European First-Movers Manage IoT Analytics Projects Successfully
Intelligence for the connected world How European First-Movers Manage IoT Analytics Projects Successfully Thomas Rohrmann, Michael Probst Analytics Experience 2016, Rome #analyticsx C opyr i g ht 2016,
More information5 Fundamental Strategies for Building a Data-centered Data Center
5 Fundamental Strategies for Building a Data-centered Data Center June 3, 2014 Ken Krupa, Chief Field Architect Gary Vidal, Solutions Specialist Last generation Reference Data Unstructured OLTP Warehouse
More informationAzure Data Lake Analytics Introduction for SQL Family. Julie
Azure Data Lake Analytics Introduction for SQL Family Julie Koesmarno @MsSQLGirl www.mssqlgirl.com jukoesma@microsoft.com What we have is a data glut Vernor Vinge (Emeritus Professor of Mathematics at
More informationVishesh Oberoi Seth Reid Technical Evangelist, Microsoft Software Developer, Intergen
Vishesh Oberoi Technical Evangelist, Microsoft VishO@microsoft.com @ovishesh Seth Reid Software Developer, Intergen contact@sethreid.co.nz @sethreidnz Vishesh Oberoi Technical Evangelist, Microsoft VishO@microsoft.com
More informationBig Data, Fast Data and Data Lake Concepts
Procedia Computer Science Volume 88, 2016, Pages 300 305 7th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2016 Big Data, Fast Data and Data Lake Concepts National
More informationLambda Architecture for Batch and Stream Processing. October 2018
Lambda Architecture for Batch and Stream Processing October 2018 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Notices This document is provided for informational purposes only.
More informationBuilding a Data Strategy for a Digital World
Building a Data Strategy for a Digital World Jason Hunter, CTO, APAC Data Challenge: Pushing the Limits of What's Possible The Art of the Possible Multiple Government Agencies Data Hub 100 s of Service
More informationEnable IoT Solutions using Azure
Internet Of Things A WHITE PAPER SERIES Enable IoT Solutions using Azure 1 2 TABLE OF CONTENTS EXECUTIVE SUMMARY INTERNET OF THINGS GATEWAY EVENT INGESTION EVENT PERSISTENCE EVENT ACTIONS 3 SYNTEL S IoT
More informationBI ENVIRONMENT PLANNING GUIDE
BI ENVIRONMENT PLANNING GUIDE Business Intelligence can involve a number of technologies and foster many opportunities for improving your business. This document serves as a guideline for planning strategies
More informationData 101 Which DB, When Joe Yong Sr. Program Manager Microsoft Corp.
17-18 March, 2018 Beijing Data 101 Which DB, When Joe Yong Sr. Program Manager Microsoft Corp. The world is changing AI increased by 300% in 2017 Data will grow to 44 ZB in 2020 Today, 80% of organizations
More informationBIG DATA COURSE CONTENT
BIG DATA COURSE CONTENT [I] Get Started with Big Data Microsoft Professional Orientation: Big Data Duration: 12 hrs Course Content: Introduction Course Introduction Data Fundamentals Introduction to Data
More informationReal-time Analytics with Azure Stream Analytics. Michael
Real-time Analytics with Azure Stream Analytics Michael Johnson @MikeJohnsonZA What I d like to share with you today Introduction to streaming data Overview of Azure Steam Analytics Demonstrate a simple
More informationAlexander Klein. ETL in the Cloud
Alexander Klein ETL in the Cloud Sponsors help us to run this event! THX! You Rock! Sponsor Gold Sponsor Silver Sponsor Bronze Sponsor You Rock! Sponsor Session 13:45 Track 1 Das super nerdige Solisyon
More informationPřehled 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
More informationBIG DATA TECHNOLOGIES: WHAT EVERY MANAGER NEEDS TO KNOW ANALYTICS AND FINANCIAL INNOVATION CONFERENCE JUNE 26-29,
BIG DATA TECHNOLOGIES: WHAT EVERY MANAGER NEEDS TO KNOW ANALYTICS AND FINANCIAL INNOVATION CONFERENCE JUNE 26-29, 2016 1 OBJECTIVES ANALYTICS AND FINANCIAL INNOVATION CONFERENCE JUNE 26-29, 2016 2 WHAT
More informationTopics. Big Data Analytics What is and Why Hadoop? Comparison to other technologies Hadoop architecture Hadoop ecosystem Hadoop usage examples
Hadoop Introduction 1 Topics Big Data Analytics What is and Why Hadoop? Comparison to other technologies Hadoop architecture Hadoop ecosystem Hadoop usage examples 2 Big Data Analytics What is Big Data?
More information