Power BI : Deep Dive

NOVEMBER 2015

Presented By:Ashish Jagdale - Data AnalystAnkita Anchan - BI DeveloperAnil Shah - Managing Partner

Agenda• Quick Recap on Previous Power BI Webinar

• Azure Data Factory• Introduction to Azure Data Factory• Supported Data Stores• Azure Data Factory Demo• Pricing • Data Factory Limits

• Power BI Updates• Power BI Desktop Tool• Power BI Online

• Q & A

Quick RecapWhat’s New in Power BI – JUNE 2015

Video Recording: https://www.youtube.com/watch?v=ROQ_MFgjTUA

Power BI Deep Dive & Real-Time Analytics – AUGUST 2015

Video Recording: https://www.youtube.com/watch?v=MkIM2aVqRa8

Power BI : Features Deep Dive – SEPTEMBER 2015

Video Recording: https://www.youtube.com/watch?v=4QcrfNJvRVo

Power BI : Features Deep Dive –OCTOBER 2015

Video Recording: https://www.youtube.com/watch?v=wIpwziw2Y4s&feature=youtu.be

Introduction to Azure Data FactoryWhat is Azure Data Factory?• Cloud-based, highly scalable data movement and transformation tool• Build on Azure for integrating all kinds of data• ADF can be accessed using Azure Preview Portal (portal.azure.com)

Key Concepts in Azure Data Factory• Dataset – Identify data structures within different data stores including tables, files, folders, and documents

• Linked Service – Define the information needed for Data Factory to connect to external resources

• Pipeline – Used to group activities into a unit that together perform a task

• Activity – Define the actions to perform on your data

Contd..

Fig. Relationships between Dataset, Activity, Pipeline, and Linked service

Contd..

Fig. Collect data from many different on-premises data sources, ingest and prepare it, organize and analyze it with a range of transformations, then publish ready-to-use data for consumption

Supported Data Stores• Copy activity copies data from a source data store to a sink data store.

Data factory supports the following data stores:

Azure Data Factory - Supported Data Stores

Cloud On-Premises

Azure Blob File System

Azure Table SQL Server

Azure SQL Database Oracle Database

Azure SQL Data Warehouse MySQL Database

Azure DocumentDB DB2 Database

Azure Data Lake Store Teradata Database

SQL Server on IaaS Sybase Database

Azure Data Factory DemoDemo consists of copy data activity from csv file stored in Azure Blob Storage to Azure SQL Database using Azure Data Factory Editor

Steps for creating Azure Data Factory using Data Factory Editor• Step 1: Create an Azure Data Factory• Step 2: Create linked services• Step 3: Create input and output tables• Step 4: Create and run a pipeline• Step 5: Monitor the datasets and pipeline

Pricing• Azure Data Factory is priced by the frequency of activities (high or

low) and where the activities run (cloud or on-premises)

• Data Movement

• Inactive Pipelines - $0.80/month

Source/Target Low Frequency High FrequencyCloud $0.60 per activity per month $0.80 per activity per month

On-Premises $1.50 per activity per month $2.50 per activity per month

Cloud On-Premises

$0.25 per hour $0.10 per hour

Data Factory LimitsResource Default Limit Maximum Limit

pipelines within a data factory 100 2500

datasets within a data factory 500 5000

concurrent slices per dataset 10 10

• Data Factory is available in US West and North Europe. The compute and storage services used by data factories can be in other regions

Azure Data Factory Limits

Power BI UpdatesPower BI Desktop Tool

• Refresh single table (vs. all) for reports and data views

• Improvements in slicer visualization

• The new word cloud visualization

Contd..Power BI Online

• Group: Member/Admin

• Duplicate report page

ANY QUERIES?

Our next Power BI webinar to be scheduled on 17th December 2015

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