Most popular
Introduction to Apache Spark Essentials (TTSK7502)
What you'll learn
The essentials of Spark architecture and applications
How to execute Spark Programs
How to create and manipulate both RDDs (Resilient Distributed Datasets) and UDFs (Unified Data Frames)
How Spark core components come together for complete applications
Tableau Desktop (TTDTAB007)
What you'll learn
Use next-level features within the Tableau interface / paradigm to effectively create powerful, advanced level visualizations
Create advanced calculations including string manipulation, basic arithmetic calculations, custom aggregations and ratios, date math, logic statements and quick table calculations
Use groups, bins, hierarchies, sorts, sets, and filters to create focused, effective and advanced -level visualizations
Use Measure Name and Measure Value fields to create visualizations with multiple measures and dimensions
Share visualizations with others, combining visualizations into Interactive Dashboards and publish them to the web
Represent data visualization (emphasizing advanced skill areas only):
Cross tabs; Heat maps; Distribution charts; Tree maps; Pie charts and bar charts; Dual axis and combo charts with different mark types; Box plots; Highlight tables; Scatter plots
Hadoop Developer Foundations
What you'll learn
Introduction to Hadoop
HDFS
YARN
Data Ingestion
HBase
Oozie
Working with Hive
Hive advanced
Hive in Cloudera/Hortonworks Distribution (or tools of choice)
Working with Spark
Spark Basics
Spark Shell
RDDs
Spark Dataframes and Datasets
Spark SQL
Spark API programming
Spark and Hadoop
Machine Learning (ML/MLlib)
GraphX
Spark Streaming
Tableau Desktop Fundamentals (TTDTAB006)
What you'll learn
Connect to your data, and Edit and save a data source.
Understand Tableau terminology.
Connect to your data, and Edit and save a data source.
Use the Tableau interface / paradigm to effectively create powerful visualizations.
Create basic calculations including string manipulation, basic arithmetic calculations, custom aggregations and ratios, date math, logic statements and quick table calculations.
Represent your data using the following visualization types: Cross Tabs, Geographic Maps, Heat Maps, Distribution Charts, Tree Maps, Pie Charts and Bar Charts, Dual Axis and Combo Charts with different mark types, Box Plots, Highlight Tables, Scatter Plots
Use Reference Lines to highlight elements of your data.
Use groups, bins, hierarchies, sorts, sets, and filters to create focused and effective visualizations
Use Measure Name and Measure Value fields to create visualizations with multiple measures and dimensions.
Handle changes in your data source such as field addition, deletion or name changes.
Share your visualizations with others.
Combine your visualizations into Interactive Dashboards and publish them to the web.
Working with Apache Kafka
What you'll learn
Overview of Streaming technologies
Kafka concepts and architecture
Programming using Kafka API
Kafka Streams
Monitoring Kafka
Tuning/Troubleshooting Kafka
Tableau Server Administration (TTDTAB005)
What you'll learn
User interactions with Tableau Server
Tableau Server components
Single-server installation
Content administration
Authorization and permissions
Users, groups, and sites
Data sources and extracts
Schedules, tasks, and subscriptions
Monitoring server status
Command-line utilities and REST API
Upgrading a single-server installation to a new version
Modifying the authentication method
Developing with Spark for Big Data (TTSK7505)
What you'll learn
The essentials of Spark architecture and applications
How to execute Spark Programs
How to create and manipulate both RDDs (Resilient Distributed Datasets) and UDFs (Unified Data Frames)
How to persist and restore data frames
Essential NOSQL access
How to integrate machine learning into Spark applications
How to use Spark Streaming and Kafka to create streaming applications
Next Level Power BI (TTDPB02)
What you'll learn
Identify and retrieve data from data sources and understand the different connection methods.
Optimize query performance
Profile and examine the data and apply data shape transformations
Develop a scalable and performance data model
Enhance the data model with DAX using measures, calculated columns and tables
Use variables and aggregations to optimize model performance
Design and create reports and dashboards
Select and add appropriate visualizations
Create paginated reports
Perform Advanced Analytics
Create and manage workspaces
Manage datasets and dataset refresh
Apply row-level security
Intermediate
55164-A: Quick Powerful Graphics with Power View, PowerPivot, Power Query, Power Map and Power BI
$1,590.00
55164-A: Quick Powerful Graphics with Power View, PowerPivot, Power Query, Power Map and Power BI
What you'll learn
Navigate the Power View interface.
Utilize Power View reports.
Work with tables.
Understand aggregations.
Utilize matrix.
Configure drill through.
Use cards as a visualization.
Apply filters.
Create charts.
Utilize tiles.
Add slicers to reports.
Utilize themes.
Navigate the PowerPivot interface.
Examine and configure relationships.
Configure calculated columns are calculated fields.
Create PivotTables.
Understand and utilize DAX.
Work with hierarchies.
Manage perspectives.
Navigate the Power Query interface.
Merge datasets.
Manage modifications.
Perform data cleaning.
Navigate the Power Map interface.
Use Bing maps.
Examine map data.
Configure tours, scenes, and layers.
Add time to a presentation.
Navigate the Power BI interface.
Utilize data sources.
Understand querying with natural language.
Successfully log into their virtual machine.
Have a full understanding of what the course intends to cover.
Apache Spark for Data Scientists
What you'll learn
The essentials of Spark architecture and applications
How to execute Spark Programs
How to create and manipulate both RDDs (Resilient Distributed Datasets) and UDFs (Unified Data Frames)
How to integrate machine learning into Spark applications
How to use Spark Streaming
Trending
Introduction to Apache Spark Essentials (TTSK7502)
What you'll learn
The essentials of Spark architecture and applications
How to execute Spark Programs
How to create and manipulate both RDDs (Resilient Distributed Datasets) and UDFs (Unified Data Frames)
How Spark core components come together for complete applications
Tableau Desktop (TTDTAB007)
What you'll learn
Use next-level features within the Tableau interface / paradigm to effectively create powerful, advanced level visualizations
Create advanced calculations including string manipulation, basic arithmetic calculations, custom aggregations and ratios, date math, logic statements and quick table calculations
Use groups, bins, hierarchies, sorts, sets, and filters to create focused, effective and advanced -level visualizations
Use Measure Name and Measure Value fields to create visualizations with multiple measures and dimensions
Share visualizations with others, combining visualizations into Interactive Dashboards and publish them to the web
Represent data visualization (emphasizing advanced skill areas only):
Cross tabs; Heat maps; Distribution charts; Tree maps; Pie charts and bar charts; Dual axis and combo charts with different mark types; Box plots; Highlight tables; Scatter plots
Hadoop Developer Foundations
What you'll learn
Introduction to Hadoop
HDFS
YARN
Data Ingestion
HBase
Oozie
Working with Hive
Hive advanced
Hive in Cloudera/Hortonworks Distribution (or tools of choice)
Working with Spark
Spark Basics
Spark Shell
RDDs
Spark Dataframes and Datasets
Spark SQL
Spark API programming
Spark and Hadoop
Machine Learning (ML/MLlib)
GraphX
Spark Streaming
Tableau Desktop Fundamentals (TTDTAB006)
What you'll learn
Connect to your data, and Edit and save a data source.
Understand Tableau terminology.
Connect to your data, and Edit and save a data source.
Use the Tableau interface / paradigm to effectively create powerful visualizations.
Create basic calculations including string manipulation, basic arithmetic calculations, custom aggregations and ratios, date math, logic statements and quick table calculations.
Represent your data using the following visualization types: Cross Tabs, Geographic Maps, Heat Maps, Distribution Charts, Tree Maps, Pie Charts and Bar Charts, Dual Axis and Combo Charts with different mark types, Box Plots, Highlight Tables, Scatter Plots
Use Reference Lines to highlight elements of your data.
Use groups, bins, hierarchies, sorts, sets, and filters to create focused and effective visualizations
Use Measure Name and Measure Value fields to create visualizations with multiple measures and dimensions.
Handle changes in your data source such as field addition, deletion or name changes.
Share your visualizations with others.
Combine your visualizations into Interactive Dashboards and publish them to the web.
Working with Apache Kafka
What you'll learn
Overview of Streaming technologies
Kafka concepts and architecture
Programming using Kafka API
Kafka Streams
Monitoring Kafka
Tuning/Troubleshooting Kafka
Tableau Server Administration (TTDTAB005)
What you'll learn
User interactions with Tableau Server
Tableau Server components
Single-server installation
Content administration
Authorization and permissions
Users, groups, and sites
Data sources and extracts
Schedules, tasks, and subscriptions
Monitoring server status
Command-line utilities and REST API
Upgrading a single-server installation to a new version
Modifying the authentication method
Developing with Spark for Big Data (TTSK7505)
What you'll learn
The essentials of Spark architecture and applications
How to execute Spark Programs
How to create and manipulate both RDDs (Resilient Distributed Datasets) and UDFs (Unified Data Frames)
How to persist and restore data frames
Essential NOSQL access
How to integrate machine learning into Spark applications
How to use Spark Streaming and Kafka to create streaming applications
Next Level Power BI (TTDPB02)
What you'll learn
Identify and retrieve data from data sources and understand the different connection methods.
Optimize query performance
Profile and examine the data and apply data shape transformations
Develop a scalable and performance data model
Enhance the data model with DAX using measures, calculated columns and tables
Use variables and aggregations to optimize model performance
Design and create reports and dashboards
Select and add appropriate visualizations
Create paginated reports
Perform Advanced Analytics
Create and manage workspaces
Manage datasets and dataset refresh
Apply row-level security
Intermediate
55164-A: Quick Powerful Graphics with Power View, PowerPivot, Power Query, Power Map and Power BI
$1,590.00
55164-A: Quick Powerful Graphics with Power View, PowerPivot, Power Query, Power Map and Power BI
What you'll learn
Navigate the Power View interface.
Utilize Power View reports.
Work with tables.
Understand aggregations.
Utilize matrix.
Configure drill through.
Use cards as a visualization.
Apply filters.
Create charts.
Utilize tiles.
Add slicers to reports.
Utilize themes.
Navigate the PowerPivot interface.
Examine and configure relationships.
Configure calculated columns are calculated fields.
Create PivotTables.
Understand and utilize DAX.
Work with hierarchies.
Manage perspectives.
Navigate the Power Query interface.
Merge datasets.
Manage modifications.
Perform data cleaning.
Navigate the Power Map interface.
Use Bing maps.
Examine map data.
Configure tours, scenes, and layers.
Add time to a presentation.
Navigate the Power BI interface.
Utilize data sources.
Understand querying with natural language.
Successfully log into their virtual machine.
Have a full understanding of what the course intends to cover.
Apache Spark for Data Scientists
What you'll learn
The essentials of Spark architecture and applications
How to execute Spark Programs
How to create and manipulate both RDDs (Resilient Distributed Datasets) and UDFs (Unified Data Frames)
How to integrate machine learning into Spark applications
How to use Spark Streaming
Featured Courses
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PL-300: Microsoft Power BI Data Analyst
Course Description: This course will discuss the various methods and …
Featured
CompTIA Data+
Course Description As the importance of data analytics grows, more …
CompTIA Data+
What you'll learn
CompTIA Data+ gives you the confidence to bring data analysis to life
Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle
Mining data
Manipulating data
Visualizing and reporting data
Applying basic statistical methods
All Analytics & BI Courses
Analytics & Business Intelligence Online Training Courses - Live
An organization’s analytics and data management initiatives require a broad range of skills across a broad range of technologies and processes. Our courses are taught by industry experts who bring real-life knowledge and experience to the classroom. They help students:
- visualize critical information
- discover new patterns and trends
- mine and integrate data from disparate sources
- optimize data models
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Introduction to Power BI (TTDPB01)
QuickStart to Power BI for Analysts and Users is a …
What you'll learn
Perform Power BI desktop data transformation.
Describe Power BI desktop modelling.
Create a Power BI desktop visualization.
Implement the Power BI service.
Describe how to connect to Excel data.
Shape and Combine Data
Describe how to collaborate with Power BI data.
Connect directly to data stores.
Time Permitting: Explore the Power BI developer API.
Time Permitting: Describe the Power BI mobile app
Next Level Power BI (TTDPB02)
Next Level Power BI for Experienced Users is a two-day …
What you'll learn
Identify and retrieve data from data sources and understand the different connection methods.
Optimize query performance
Profile and examine the data and apply data shape transformations
Develop a scalable and performance data model
Enhance the data model with DAX using measures, calculated columns and tables
Use variables and aggregations to optimize model performance
Design and create reports and dashboards
Select and add appropriate visualizations
Create paginated reports
Perform Advanced Analytics
Create and manage workspaces
Manage datasets and dataset refresh
Apply row-level security
Tableau Server Administration (TTDTAB005)
Tableau Server Administration is a two-day course that provides new …
What you'll learn
User interactions with Tableau Server
Tableau Server components
Single-server installation
Content administration
Authorization and permissions
Users, groups, and sites
Data sources and extracts
Schedules, tasks, and subscriptions
Monitoring server status
Command-line utilities and REST API
Upgrading a single-server installation to a new version
Modifying the authentication method
Tableau Desktop Fundamentals (TTDTAB006)
Tableau Desktop Fundamentals is a two-day, hands-on course designed for …
What you'll learn
Connect to your data, and Edit and save a data source.
Understand Tableau terminology.
Connect to your data, and Edit and save a data source.
Use the Tableau interface / paradigm to effectively create powerful visualizations.
Create basic calculations including string manipulation, basic arithmetic calculations, custom aggregations and ratios, date math, logic statements and quick table calculations.
Represent your data using the following visualization types: Cross Tabs, Geographic Maps, Heat Maps, Distribution Charts, Tree Maps, Pie Charts and Bar Charts, Dual Axis and Combo Charts with different mark types, Box Plots, Highlight Tables, Scatter Plots
Use Reference Lines to highlight elements of your data.
Use groups, bins, hierarchies, sorts, sets, and filters to create focused and effective visualizations
Use Measure Name and Measure Value fields to create visualizations with multiple measures and dimensions.
Handle changes in your data source such as field addition, deletion or name changes.
Share your visualizations with others.
Combine your visualizations into Interactive Dashboards and publish them to the web.
Tableau Desktop (TTDTAB007)
Geared for experienced Tableau, Tableau Desktop II / Intermediate Tableau …
What you'll learn
Use next-level features within the Tableau interface / paradigm to effectively create powerful, advanced level visualizations
Create advanced calculations including string manipulation, basic arithmetic calculations, custom aggregations and ratios, date math, logic statements and quick table calculations
Use groups, bins, hierarchies, sorts, sets, and filters to create focused, effective and advanced -level visualizations
Use Measure Name and Measure Value fields to create visualizations with multiple measures and dimensions
Share visualizations with others, combining visualizations into Interactive Dashboards and publish them to the web
Represent data visualization (emphasizing advanced skill areas only):
Cross tabs; Heat maps; Distribution charts; Tree maps; Pie charts and bar charts; Dual axis and combo charts with different mark types; Box plots; Highlight tables; Scatter plots
Advanced Tableau | Advanced Data Visualization, Calculations, Analytics, Integration with Hadoop (TTDTAB025)
Geared for experienced Tableau users with data analysis background and …
What you'll learn
Why Data Visualization is Needed?
Connecting to the databases and make basic charts and graphs.
How to make Advance Charts and Graphs.
Scripting functionality and organizing data for effective results
More advanced visualizations for various analytical requirements
Creating Time based calculations.
Using location analytics capabilities to put geographic and other spatial context to your analysis.
Blending and arranging data from multiple source systems for effective analysis.
How to Integrate Tableau with R and Hadoop, Statistical Analytics, and social media analytics.
Working in real time environment for Tableau Projects leveraging the course mini project.
The requirement and creating various dashboards, story boards, deploying your dashboards for the project.
Featured
-35%
PL-300: Microsoft Power BI Data Analyst
Course Description: This course will discuss the various methods and …
Featured
CompTIA Data+
Course Description As the importance of data analytics grows, more …
What you'll learn
CompTIA Data+ gives you the confidence to bring data analysis to life
Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle
Mining data
Manipulating data
Visualizing and reporting data
Applying basic statistical methods
