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OAC Workshop - From A to Z

A23789f299ed06fe7d9f1c6940440bfa?s=47 FTisiot
March 12, 2019

OAC Workshop - From A to Z

A23789f299ed06fe7d9f1c6940440bfa?s=128

FTisiot

March 12, 2019
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  1. info@rittmanmead.com www.rittmanmead.com @rittmanmead Oracle Analytics Cloud Workshop AnD Summit 2019

  2. info@rittmanmead.com www.rittmanmead.com @rittmanmead !2 Francesco Tisiot BI Tech Lead at

    Rittman Mead Verona, Italy Rittman Mead Blog 10 Years Experience in BI/Analytics francesco.tisiot@rittmanmead.com @FTisiot Oracle ACE
  3. info@rittmanmead.com www.rittmanmead.com @rittmanmead About Rittman Mead !3 Rittman Mead is

    a data and analytics company who specialise in data visualisation, predictive analytics, enterprise reporting and data engineering. We use our skill, experience and know-how to work with organisations across the world to interpret their data. We enable the business, the consumers, the data providers and IT to work towards a common goal, delivering innovative and cost-effective solutions based on our core values of thought leadership, hard work and honesty. We work across multiple verticals on projects that range from mature, large scale implementations to proofs of concept and can provide skills in development, architecture, delivery, training and support.
  4. info@rittmanmead.com www.rittmanmead.com @rittmanmead !4 •OAC Overview •Versions, Licensing and Provisioning

    •Migrating to the Cloud •Importing Data Sources •Mode 1 and Mode 2 Overview •Report Writing •Oracle DV •Mashups, Dataflow and OAC Integration •Advanced Analytics / Machine Learning Course Agenda
  5. info@rittmanmead.com www.rittmanmead.com @rittmanmead INTRO 101 - OAC Overview and Features

    Comparison
  6. info@rittmanmead.com www.rittmanmead.com @rittmanmead !6 •OAC Product Overview •OAC Key Components

    •OAC Comparison to OBIEE Agenda - OAC Overview
  7. info@rittmanmead.com www.rittmanmead.com @rittmanmead !7 •Analytics “Platform” •Fully scalable •Can be

    used in the cloud, on premise or data centre Oracle Analytics Cloud Service
  8. info@rittmanmead.com www.rittmanmead.com @rittmanmead !8 • Functionality includes (but not limited

    to): ‣ Oracle Cloud ‘My Services’ - Used to create instances (similar to SSI’s in OBIEE 12c) ‣ Oracle Analytics Cloud Console - Used to manage datasources - Manage Users - Manage Backups/Restores via snapshots ‣ Enterprise Reporting (BICS) - OBI Data Models (RPD) - BI Publisher - OBIEE Analysis/Dashboards ‣ Oracle Data Visualiser - Data Discovery, Visualisation and Storyboarding - Mashups - Data preparation Oracle Analytics Cloud Service Functionality
  9. info@rittmanmead.com www.rittmanmead.com @rittmanmead !9 •Used to manage the platform •Track

    Billing •User Metrics •Environment Up/Down Time Oracle Cloud ‘My Services’
  10. info@rittmanmead.com www.rittmanmead.com @rittmanmead !10 •Web based management tool ‣Manages: -DV

    Projects -Data Sources -Data Sets -Users -Application Roles Oracle Analytics Cloud Console
  11. info@rittmanmead.com www.rittmanmead.com @rittmanmead !11 •OBIEE in the cloud •Lift and

    Shift from existing OBIEE instances •Full functional Analysis & Dashboards OAC Enterprise Reporting
  12. info@rittmanmead.com www.rittmanmead.com @rittmanmead !12 •Dynamically visualise data as you drag

    and drop attributes and measures •Quickly create visualisations to distribute to other users •Use custom data sources, e.g. spreadsheets or database •Also includes Data Visualiser Desktop OAC Oracle Data Visualiser
  13. info@rittmanmead.com www.rittmanmead.com @rittmanmead !13 •Import Data from Files or Database

    •Create Relationships •Add Data Filters •Add Calculations OAC Data Visualisation - Data Preparation
  14. info@rittmanmead.com www.rittmanmead.com @rittmanmead !14 Two Service Options Analytics Cloud Classic

    Analytics Cloud Services managed by Oracle: Backup & Recovery Service Monitoring Patching & Upgrades Test & Production instances Based on Oracle Cloud Infrastructure (OCI) Services managed by You: Based on Oracle Cloud Infrastructure Classic
  15. info@rittmanmead.com www.rittmanmead.com @rittmanmead !15 Three Edition Options Enterprise Edition Data

    Lake Edition Standard Edition Data Discovery Data Preparation What-If Planning Big Data Storage Data Transformation via Apache Spark Data Lake Connectivity Enterprise Analysis & Dashboarding Published Reporting Day by Day
  16. info@rittmanmead.com www.rittmanmead.com @rittmanmead !16 Two Purchasing Options Monthly Flex Pay

    As You Go Based on Universal Credits model No minimum tenure Payments made in arrears Based on consumption Suitable for: Rapid Prototyping Testing & Sampling Elastic Scalable Based on Universal Credits model 12 month minimum tenure Payments made in advance Unused credits are forfeited Suitable for: Predictable, production workloads Long running platforms
  17. info@rittmanmead.com www.rittmanmead.com @rittmanmead !17 • OAC instances are provisioned in

    Oracle Compute Units (OCPU’s) shapes to satisfy different requirements • The shape can be altered after service creation ‣ Flex capacity up (or down) based on immediate need Several Shape Options
  18. info@rittmanmead.com www.rittmanmead.com @rittmanmead !18 • Mobile Web & BI Mobile

    App ‣ All DV projects will auto-render on mobile devices ‣ The heritage mobile app supports all OAC content • Synopsis Mobile App ‣ Automatic Excel/CSV ingestion & analysis ‣ Extending to all DV supported sources • Day by Day ‣ Included within Enterprise Edition ‣ Search driven analytics ‣ Voice recognition allows you to verablise questions ‣ Embedded learning enables a tailored experience Mobile Options
  19. info@rittmanmead.com www.rittmanmead.com @rittmanmead !19 • Secure Access ‣ Remote hosts

    access cloud via SSH ‣ Specific access rules can be configured Security & Access • Users & Roles in OAC can be managed via two methods: ‣ Embedded Weblogic LDAP server ‣ Oracle Identity Cloud Service (IDCS) - Shared model across all cloud services - Supports SSO - Enables AD integration ‣ IDCS only relevant for Universal Credit
  20. dimensionality.ch info@rittmanmead.com christian.berg@dimensionality.ch Architectural Options

  21. dimensionality.ch info@rittmanmead.com christian.berg@dimensionality.ch !21 Oracle Cloud • Simplest integration architecture:

    ‣ Data held in Oracle Database Cloud Service (DBCS) ‣ ETL via Oracle Data Integration Platform Cloud (DIPC) • Data acquisition from Cloud Applications: ‣ BI Cloud Connector ‣ Goldengate ‣ OAC’s new Data Replication features • Data acquisition from on-premises applications: ‣ Data Sync ‣ APEX Data Loader ‣ SQL Developer tools ‣ Data Pump
  22. dimensionality.ch info@rittmanmead.com christian.berg@dimensionality.ch !22 Hybrid • Database remains on-premises ‣

    Frequently a staging post for full migration • Data access via Remote Data Connector ‣ Runs on dedicated application server (WLS/Tomcat) ‣ Secure connectivity via public/private SSL key ‣ Supports Oracle, DB2, Teradata, SQL Server • Beware performance challenges ‣ Potential latency due to network bandwidth ‣ Check network capacity and test carefully
  23. dimensionality.ch info@rittmanmead.com christian.berg@dimensionality.ch !23 Multi-Cloud • Commonly adopted cloud strategy

    ‣ Spread investment across different cloud environments ‣ Mix private and public cloud workloads • Data Sets have a broad support for connectivity ‣ Relational, Big Data, Semi-structured & proprietry • Data Model supports fewer options (via RDC) ‣ Oracle, DB2, Terdata, SQL Server
  24. info@rittmanmead.com www.rittmanmead.com @rittmanmead Getting Started With Your First Instance

  25. info@rittmanmead.com www.rittmanmead.com @rittmanmead !25 Two Service Options Analytics Cloud Classic

    Analytics Cloud Services managed by Oracle: Backup & Recovery Service Monitoring Patching & Upgrades Test & Production instances Based on Oracle Cloud Infrastructure (OCI) Services managed by You: Based on Oracle Cloud Infrastructure Classic
  26. info@rittmanmead.com www.rittmanmead.com @rittmanmead !26 Analytics Cloud (OAC)

  27. info@rittmanmead.com www.rittmanmead.com @rittmanmead !27 Analytics Cloud (OAC)

  28. info@rittmanmead.com www.rittmanmead.com @rittmanmead !28 Real Provisioning Example - OAC

  29. info@rittmanmead.com www.rittmanmead.com @rittmanmead !29 Real Provisioning Example - OAC

  30. info@rittmanmead.com www.rittmanmead.com @rittmanmead !30 Real Provisioning Example - OAC Choose

    Edition Choose Feature Set
  31. info@rittmanmead.com www.rittmanmead.com @rittmanmead !31 Real Provisioning Example - OAC

  32. info@rittmanmead.com www.rittmanmead.com @rittmanmead !32 Real Provisioning Example - OAC

  33. info@rittmanmead.com www.rittmanmead.com @rittmanmead !33 Real Provisioning Example - OAC

  34. info@rittmanmead.com www.rittmanmead.com @rittmanmead !34 Real Provisioning Example - OACC Provisioning

    1 - Database 2 - OACC
  35. info@rittmanmead.com www.rittmanmead.com @rittmanmead !35 Real Provisioning Example - OACC -

    Database
  36. info@rittmanmead.com www.rittmanmead.com @rittmanmead !36 Choose Region Real Provisioning Example -

    OACC - Database * Must match the Region Chosen in OACC
  37. info@rittmanmead.com www.rittmanmead.com @rittmanmead !37 Real Provisioning Example - OACC -

    Database
  38. info@rittmanmead.com www.rittmanmead.com @rittmanmead !38 Choose Backup Options Real Provisioning Example

    - OACC - Database
  39. info@rittmanmead.com www.rittmanmead.com @rittmanmead !39 Real Provisioning Example - OACC -

    Database
  40. info@rittmanmead.com www.rittmanmead.com @rittmanmead !40 Real Provisioning Example - OACC

  41. info@rittmanmead.com www.rittmanmead.com @rittmanmead !41 Real Provisioning Example - OACC

  42. info@rittmanmead.com www.rittmanmead.com @rittmanmead !42 Real Provisioning Example - OACC

  43. info@rittmanmead.com www.rittmanmead.com @rittmanmead !43 Real Provisioning Example - OACC Choose

    Region * Must match the Region Chosen in ODBCS
  44. info@rittmanmead.com www.rittmanmead.com @rittmanmead !44 Real Provisioning Example - OACC Choose

    Edition
  45. info@rittmanmead.com www.rittmanmead.com @rittmanmead !45 Real Provisioning Example - OACC

  46. info@rittmanmead.com www.rittmanmead.com @rittmanmead !46 Real Provisioning Example - OACC

  47. info@rittmanmead.com www.rittmanmead.com @rittmanmead !47 Real Provisioning Example - OACC

  48. info@rittmanmead.com www.rittmanmead.com @rittmanmead !48 Real Provisioning Example - OACC

  49. info@rittmanmead.com www.rittmanmead.com @rittmanmead !49 Real Provisioning Example - OACC

  50. info@rittmanmead.com www.rittmanmead.com @rittmanmead Moving from on-premises OBIEE to OAC

  51. info@rittmanmead.com www.rittmanmead.com @rittmanmead •Cloud is “in” – management support assured

    •No need to involve internal IT and slow processes •Scale up and down as needed •Pay as you go – down to hourly basis •No capital expenses, only operating expenses! •“Fight for budget” a lot smoother Why to move to cloud
  52. info@rittmanmead.com www.rittmanmead.com @rittmanmead •OAC and OACC contain DV •OBIEE requires

    additional license for DV •“Cloud first” strategy means cloud gets new features earlier Why to move to cloud
  53. info@rittmanmead.com www.rittmanmead.com @rittmanmead •Choose whether to use RPD or thin

    client modeller ‣Less dependency on skilled staff ‣Free up skilled staff for core tasks ‣Leave common tasks to super users ‣RPD and Admin Tool still there ‣Leverage existing know-how! Why to move to cloud
  54. info@rittmanmead.com www.rittmanmead.com @rittmanmead Thin client modeller and Admin Tool

  55. info@rittmanmead.com www.rittmanmead.com @rittmanmead Thin client modeller and Admin Tool

  56. info@rittmanmead.com www.rittmanmead.com @rittmanmead Your ETL Toolset

  57. info@rittmanmead.com www.rittmanmead.com @rittmanmead Your ETL toolset or Data Flows

  58. info@rittmanmead.com www.rittmanmead.com @rittmanmead !58 • Migrating to OAC is relatively

    straight forwards ‣ The method depends on your starting point… Migration Options From BICS Create BAR File * Upload Based on Oracle Cloud Infrastructure Classic 11g Run the Migration Tool Deploy Import Bundle to OAC Minimum OBIEE 11.1.1.7 Does not apply to Autonomous version Manual Identity Store configuration 12c Create 12c BAR file Upload Snapshot to OAC or Manually upload Data Model Archive/Unarchive Web Catalog
  59. info@rittmanmead.com www.rittmanmead.com @rittmanmead !59 • DVCS to OAC/OACC ‣ Both

    BICS and DVCS not sold anymore ‣ Must be migrated at some point • OAC/OACC to on-premises ‣ On-premises won’t go away ‣ Allow for easier / cheaper on-boarding and development • OACC has full accessibility • Supports all devops and lifecycle technologies known from OBIEE Migration Options
  60. info@rittmanmead.com www.rittmanmead.com @rittmanmead •Clean and correct first! •Old 11g was

    a lot more permissive and fuzzy on certain rules •Clean on-premises means fluid migration •Fix-in-cloud often a lot harder •Review and reconsider your security •Eliminate legacy burdens •Trim unused excess •Institute standards Migration Considerations
  61. info@rittmanmead.com www.rittmanmead.com @rittmanmead INTRO 101 - OAC Overview and Features

    Comparison
  62. info@rittmanmead.com www.rittmanmead.com @rittmanmead DATASOURCE101 - Creating New OAC Datasources

  63. info@rittmanmead.com www.rittmanmead.com @rittmanmead !63 •OAC can access data sources from

    the cloud or on premise (depending on licensing) •Some examples of data sources are: ‣Oracle Database ‣Oracle Essbase ‣Hive ‣Impala ‣MySQL ‣SQL Server ‣Amazon Redshift ‣ODBC ‣and many more! Oracle Analytics Cloud Data Sources
  64. info@rittmanmead.com www.rittmanmead.com @rittmanmead !64 •New Data Sources (Connections) are added

    through the Oracle Analytics Cloud Dashboard •Uses a Wizard to create the data sources, and then are available for use by anyone who has access Oracle Analytics Cloud Data Sources
  65. info@rittmanmead.com www.rittmanmead.com @rittmanmead !65 •Once you have created a data

    source, you can create a Data Set. Which can be: ‣A Database Object (Table, View, etc) ‣File (Excel, CSV, etc) ‣Essbase Application ‣SQL Statements •Data Sets can be filtered to remove data that is not required •Data Sets are managed within Visual Analyzer Oracle Analytics Cloud Data Sets
  66. info@rittmanmead.com www.rittmanmead.com @rittmanmead !66 •Once you have created a data

    set, this can be used inside Visual Analyzer to create a project and visualisations based on that data Oracle Analytics Cloud Data Sets
  67. info@rittmanmead.com www.rittmanmead.com @rittmanmead !67 •Oracle BICS Remote Data Connector ‣Oracle

    Business Intelligence Cloud Service Remote Data Connector (BICS RDC) enables querying data residing in on-premises relational sources without moving data to cloud. ‣Requires a Weblogic/Tomcat Server to host application •Oracle BICS Data Sync ‣Oracle Business Intelligence Cloud Service Data Sync supports loading data from files, on premise and cloud sources into schema provisioned on Oracle Business Intelligence Cloud Service. ‣Java based service that is installed on a server. Oracle Analytics Cloud Data Sets
  68. info@rittmanmead.com www.rittmanmead.com @rittmanmead !68 •In Oracle Analytics Cloud Dashboard ‣Navigate

    to the data tab ‣Click the ‘Create’ Button ‣Choose ‘Connection’ Example Connection & Dataset: Step 1
  69. info@rittmanmead.com www.rittmanmead.com @rittmanmead !69 •On the ‘Create Connection’ dialogue ‣Select

    the data source type required (e.g. Oracle Database) Example Connection & Dataset: Step 2
  70. info@rittmanmead.com www.rittmanmead.com @rittmanmead !70 •On the ‘Create Connection’ form ‣Enter

    the details of the Connection ‣This will vary depending on the type ‣Click Save Example Connection & Dataset: Step 3
  71. info@rittmanmead.com www.rittmanmead.com @rittmanmead !71 •This will then be displayed on

    the Data tab under Connections Example Connection & Dataset: Step 4
  72. info@rittmanmead.com www.rittmanmead.com @rittmanmead !72 •Next we need to create our

    Data Set •This is done from the data tab, using the same ‘Create’ menu we used before Example Connection & Dataset: Step 5
  73. info@rittmanmead.com www.rittmanmead.com @rittmanmead !73 •Since we have used an Oracle

    connection, we get a list of available schemas. •Double-click on the schema to continue Example Connection & Dataset: Step 6
  74. info@rittmanmead.com www.rittmanmead.com @rittmanmead !74 •We then get a list of

    database objects we can choose and search through •We can also add individual columns •Data Sets are saved as objects in the OAC Dashboard Example Connection & Dataset: Step 7
  75. info@rittmanmead.com www.rittmanmead.com @rittmanmead !75 •Repeat this for any other data

    sets that may be required •We can also add filters to data sets Example Connection & Dataset: Step 8
  76. info@rittmanmead.com www.rittmanmead.com @rittmanmead !76 •Once this has been completed we

    can see the two new data sets in the Oracle Analytics Cloud Desktop under Data \ Data Sets Example Connection & Dataset: Step 9
  77. info@rittmanmead.com www.rittmanmead.com @rittmanmead !77 •These data sets can then be

    used inside Visual Analyser projects ‣more on this later! Example Connection & Dataset: Step 10
  78. info@rittmanmead.com www.rittmanmead.com @rittmanmead DATASOURCE101 - Creating New OAC Datasources

  79. info@rittmanmead.com www.rittmanmead.com @rittmanmead !79 •OAC URL: http://ritt.md/BIWA2019 •User: training •Pwd:

    Password01!! •Labs: http://ritt.md/BIWA-Labs Environment
  80. info@rittmanmead.com www.rittmanmead.com @rittmanmead DATASOURCE101 Lab 1 - Creating a new

    Connection and Data Set
  81. info@rittmanmead.com www.rittmanmead.com @rittmanmead DATAVIZ 101 - OAC Data Visualization

  82. info@rittmanmead.com www.rittmanmead.com @rittmanmead !82 Exploration: • Scattered data • Uncertainty

    • Hypothesis testing • Why did this happen • Detailed analysis • Learning from data • Analysis follows data Oracle Analytics Cloud Data Visualization Explanation: • Consolidated data • Certainty • Hypothesis confirmation • What happened • High level metrics • Teaching with data • Data guides analysis
  83. info@rittmanmead.com www.rittmanmead.com @rittmanmead !83 Data Visualization (Explore): • Scattered data

    (Data mashups) • Uncertainty (Quick to build new charts, save analysis paths) • Hypothesis testing (Individual uses to test a theory) • Why did this happen (Look for patterns behind the trends) • Detailed analysis (Track multiple analysis paths) • Learning from data (fast workflow promotes creativity) • Analysis follows data (Try many things, save false starts, unlimited filter combos) Oracle Analytics Cloud Data Visualization Answers (Explain): • Consolidated data (RPD) • Certainty (Format dashboards to convey known information) • Hypothesis confirmation (Company gets the single source of truth) • What happened (Show tiles of KPIs) • High level metrics (Present the most relevant information quickly) • Teaching with data (Slower workflow promotes best practice presentation) • Data guides analysis (Dashboard creator guides users with selective use of drill down and filtering)
  84. info@rittmanmead.com www.rittmanmead.com @rittmanmead !84 • Everything placed on the canvas

    is automatically connected • Filtering ‣Global filters affect all charts • Brushing ‣Highlighting data points in one visualization highlights them in all visualizations • Drilling ‣Drilling on one visualization automatically filters the others Oracle Analytics Cloud Data Visualization
  85. info@rittmanmead.com www.rittmanmead.com @rittmanmead !85 • The subject area view is

    similar to Answers Oracle Analytics Cloud Data Visualization
  86. info@rittmanmead.com www.rittmanmead.com @rittmanmead !86 • The data exploration bar contains

    options for chart creation based on the grammar of graphics • A grammar of graphics is a tool that enables users to concisely describe the components of a graphic Oracle Analytics Cloud Data Visualization
  87. info@rittmanmead.com www.rittmanmead.com @rittmanmead !87 •The canvas displays the chart •Filters

    can be added by dropping columns into the filter view Oracle Analytics Cloud Data Visualization
  88. info@rittmanmead.com www.rittmanmead.com @rittmanmead !88 • Drag and drop a measure

    and an attribute from the subject area onto the canvas Note: Hold the ctrl key to select both at the same time • VA will automatically generate a chart for your single measure • Time attributes automatically generate line charts Oracle Analytics Cloud Data Visualization
  89. info@rittmanmead.com www.rittmanmead.com @rittmanmead !89 • Select a chart and drag

    additional measure or attributes to the data exploration bar to modify the chart’s properties • Add filters by dropping columns into the filter bar • Modify the filter to limit values Oracle Analytics Cloud Data Visualization
  90. info@rittmanmead.com www.rittmanmead.com @rittmanmead !90 • Visualizations can be dragged and

    dropped to create different layouts • Each visualization will automatically adjust its size to fill its new placement Oracle Analytics Cloud Data Visualization
  91. info@rittmanmead.com www.rittmanmead.com @rittmanmead !91 • On the menu header go

    to save/save as and give a name to your project Oracle Analytics Cloud Data Visualization
  92. info@rittmanmead.com www.rittmanmead.com @rittmanmead DATAVIZ 101 - OAC Data Visualization

  93. info@rittmanmead.com www.rittmanmead.com @rittmanmead DATAVIZ101 Lab 1 - Creating a VA

    Project
  94. info@rittmanmead.com www.rittmanmead.com @rittmanmead MASHUPS101 - Using External Data & Data

    Flows
  95. info@rittmanmead.com www.rittmanmead.com @rittmanmead !95 •Adding your own data is sometimes

    referred to as “mash-up” •Data mashups provide the ability to introduce out of band or personal data into a governed data environment. •The expectation is to continue to maintain the self-service model •The goal is to enable the behaviors with a minimum amount of intervention. •Add your own data to analyze on its own. •Add your own data as an extension to an existing subject area. Concepts
  96. info@rittmanmead.com www.rittmanmead.com @rittmanmead !96 •Create new VA project and select

    an existing or new data set and add it to the project Import External Data Source
  97. info@rittmanmead.com www.rittmanmead.com @rittmanmead !97 • data relationships Import External Data

    Source
  98. info@rittmanmead.com www.rittmanmead.com @rittmanmead !98 •Columns from external subject areas can

    be added and manipulated as before •Select measures and attributes from both subject areas then drag and drop to the visualisation and data element area: Combine External and Enterprise Data
  99. info@rittmanmead.com www.rittmanmead.com @rittmanmead !99 •To refresh data you must ensure

    that the newer spreadsheet file contains a sheet with the same name as the original one •The sheet must contain the same columns that are already matched with the subject area. •In the Data Sources pane, or the Subject Areas pane, right-click the data that you want to refresh. •Reload Data Data Refresh
  100. info@rittmanmead.com www.rittmanmead.com @rittmanmead !100 •To remove a datasource from a

    project right-click the data that you want to remove. •Select remove from Project •To permanently delete a data source right-click the data that you want to remove. •Select delete to erase the data from storage. Remove and Delete Data
  101. info@rittmanmead.com www.rittmanmead.com @rittmanmead !101 •Data flows are used to create

    ‘curated’ Data Sets ‣ Manipulate data sets to add additional columns ‣ Join Data Sets together ‣ Filter Data Sets ‣ Sentiment Analysis ‣ Machine Learning Training ‣ Create Essbase Cubes Data Flows
  102. info@rittmanmead.com www.rittmanmead.com @rittmanmead !102 • In Oracle Analytics Cloud, go

    to the Data Tab • Select Create -> Data Flow: Creating a New Data Flow: Step 1
  103. info@rittmanmead.com www.rittmanmead.com @rittmanmead !103 • A new tab will open

    and ask you to choose a starting data set (or to create a new one): Creating a New Data Flow: Step 2
  104. info@rittmanmead.com www.rittmanmead.com @rittmanmead !104 • This will take you to

    the Data Flow editor where we can start manipulating our data Creating a New Data Flow: Step 3
  105. info@rittmanmead.com www.rittmanmead.com @rittmanmead !105 • Click the + icon next

    to the data set you imported at the beginning to add a new step to your data flow ‣This will raise a context menu for the different types of steps you can use: Creating a New Data Flow: Step 4
  106. info@rittmanmead.com www.rittmanmead.com @rittmanmead !106 • Each step type has its

    own options that can be configured: Creating a New Data Flow: Step 5
  107. info@rittmanmead.com www.rittmanmead.com @rittmanmead !107 • You then need to set

    an output point to your data set ‣Data can be stored either in the cloud data storage or back to a database that you have created a connection too: Creating a New Data Flow: Step 6
  108. info@rittmanmead.com www.rittmanmead.com @rittmanmead !108 • You can then schedule the

    Data Flow to run: Creating a New Data Flow: Step 7
  109. info@rittmanmead.com www.rittmanmead.com @rittmanmead MASHUPS101 - Using External Data & Data

    Flows
  110. info@rittmanmead.com www.rittmanmead.com @rittmanmead MASHUPS101 - Lab 1 - Using External

    Data
  111. info@rittmanmead.com www.rittmanmead.com @rittmanmead AA01 - Advanced Analytics

  112. info@rittmanmead.com www.rittmanmead.com @rittmanmead !112 •Description of Metrics and Attributes Augmented

    Analytics
  113. info@rittmanmead.com www.rittmanmead.com @rittmanmead !113 Key Drivers/Anomalies

  114. What Problem are we Trying to Solve? Supervised Unsupervised “I

    want to predict the value of Y, here are some examples” “Here is a dataset, make sense out of it!” Classification Regression https://towardsdatascience.com/supervised-vs-unsupervised-learning-14f68e32ea8d Clustering
  115. info@rittmanmead.com www.rittmanmead.com @rittmanmead !115 •Data Visualization provides one click access

    to ‣Trending ‣Clustering ‣Outlier Detection ‣Forecasting BI Analyst Experience
  116. info@rittmanmead.com www.rittmanmead.com @rittmanmead !116 DataFlow Train Model

  117. info@rittmanmead.com www.rittmanmead.com @rittmanmead !117 More Detailed ML

  118. info@rittmanmead.com www.rittmanmead.com @rittmanmead !118 Which Model - Parameters To Pick?

  119. info@rittmanmead.com www.rittmanmead.com @rittmanmead !119 Select, Try, Save, Change, Try, Save

    …..
  120. info@rittmanmead.com www.rittmanmead.com @rittmanmead !120 Model Evaluation

  121. info@rittmanmead.com www.rittmanmead.com @rittmanmead !121 Model Evaluation 502/(502+896) = 64.09% 471/(471+866)=64.77%

  122. info@rittmanmead.com www.rittmanmead.com @rittmanmead !122 Use On the Fly

  123. info@rittmanmead.com www.rittmanmead.com @rittmanmead !123 Step of a Data Flow

  124. info@rittmanmead.com www.rittmanmead.com @rittmanmead AA01 - Advanced Analytics