Building Big Data Pipelines with R & Sparklyr & Power BI

  • Course provided by Udemy
  • Study type: Online
  • Starts: Anytime
  • Price: See latest price on Udemy
Udemy

Course Description

Welcome to the Building Big Data Pipelines with R & Sparklyr & PowerBI course. In this course we will be creating a big data analytics solution using big data technologies for R.


In our use case we will be working with raw earthquake data, we will be applying big data processing techniques to extract transform and load the data into usable datasets. Once we have processed and cleaned the data, we will use it as a data source for building predictive analytics and visualizations.


Power BI Desktop is a powerful data visualization tool that lets you build advanced queries, models and reports. With Power BI Desktop, you can connect to multiple data sources and combine them into a data model. This data model lets you build visuals, and dashboards that you can share as reports with other people in your organization.


Sparklyr is an open-source library that is used for processing big data in R, by providing an interface between R and Apache Spark. It allows you to take advantage of Spark's ability to process and analyze large datasets in a distributed and interactive manner. It also provides interfaces to Spark's distributed machine learning algorithms and much more.


  • You will learn how to create big data processing pipelines using R

  • You will learn machine learning with geospatial data using the Sparklyr library

  • You will learn data analysis using Sparklyr, R and Power BI

  • You will learn how to manipulate, clean and transform data using Spark dataframes

  • You will learn how to create Geo Maps in Power BI Desktop

  • You will also learn how to create dashboards in Power BI Desktop

Who this course is for:

  • R Developers at any level
  • Data Engineers at any level
  • Developers at any level
  • Machine Learning engineers at any level
  • Data Scientists at any level
  • GIS Developers at any level
  • The curious mind

Instructor

Big Data Engineering
  • 4.2 Instructor Rating
  • 264 Reviews
  • 1,277 Students
  • 13 Courses

Big Data Engineering and Consulting, involved in multiple projects ranging from Business Intelligence, Software Engineering, IoT and Big data analytics. Expertise are in building data processing pipelines in the Hadoop and Cloud ecosystems and software development.

Currently consulting at one of the top business intelligence consultancies helping clients build data warehouses, data lakes, cloud data processing pipelines and machine learning pipelines. The technologies he uses to accomplish client requirements range from Hadoop, Amazon S3, Python, Django, Apache Spark, MSBI, Microsoft Azure, SQL Server Data Tools, Talend and Elastic MapReduce.

Expected Outcomes

  1. Power BI Data Visualization R Programming Data Analysis Big Data Machine Learning Geo Mapping with ArcGIS Maps for Power BI Geospatial Machine Learning Creating Dashboards Course content 6 sections • 19 lectures • 2h 26m total length Expand all sections Introduction 1 lecture • 8min Introduction Preview 07:31 Setup and Installations 5 lectures • 31min R Installation Preview 05:10 Installing Apache Spark 12:06 Installing Java (Optional) 04:35 Testing Apache Spark Installation 02:32 Installing Sparklyr 06:31 Building the Big Data ETL Pipeline with Sparklyr 3 lectures • 31min Data Extraction 05:43 Data Transformation 17:35 Data Exporting 07:26 Big Data Machine Learning with Sparklyr 3 lectures • 37min Data Pre-processing 17:34 Building the Predictive Model 09:30 Creating the Prediction Dataset 09:35 Data Visualization with Power BI 6 lectures • 41min Installing Power BI Desktop 01:54 Loading the Data Sources 08:29 Creating a Geo Map 09:22 Creating a Donut Chart 04:53 Create an Area Chart 07:25 Create a Bar Chart 08:58 Project Source Code 1 lecture • 1min Source Code 00:02 Requirements Basic Understanding of R Programming Little or no understanding of GIS Basic understanding of Programming concepts Basic understanding of Data Basic understanding of what Machine Learning is Description Welcome to the Building Big Data Pipelines with R & Sparklyr & PowerBI course. In this course we will be creating a big data analytics solution using big data technologies for R . In our use case we will be working with raw earthquake data, we will be applying big data processing techniques to extract transform and load the data into usable datasets. Once we have processed and cleaned the data, we will use it as a data source for building predictive analytics and visualizations. Power BI Desktop is a powerful data visualization tool that lets you build advanced queries, models and reports. With Power BI Desktop, you can connect to multiple data sources and combine them into a data model. This data model lets you build visuals, and dashboards that you can share as reports with other people in your organization. Sparklyr is an open-source library that is used for processing big data in R , by providing an interface between R and Apache Spark . It allows you to take advantage of Spark's ability to process and analyze large datasets in a distributed and interactive manner. It also provides interfaces to Spark's distributed machine learning algorithms and much more. You will learn how to create big data processing pipelines using R You will learn machine learning with geospatial data using the Sparklyr library You will learn data analysis using Sparklyr, R and Power BI You will learn how to manipulate, clean and transform data using Spark dataframes You will learn how to create Geo Maps in Power BI Desktop You will also learn how to create dashboards in Power BI Desktop Who this course is for: R Developers at any level Data Engineers at any level Developers at any level Machine Learning engineers at any level Data Scientists at any level GIS Developers at any level The curious mind Show more Show less Instructor EBISYS R&D Big Data Engineering 4.2 Instructor Rating 264 Reviews 1,277 Students 13 Courses Big Data Engineering and Consulting, involved in multiple projects ranging from Business Intelligence, Software Engineering, IoT and Big data analytics. Expertise are in building data processing pipelines in the Hadoop and Cloud ecosystems and software development. Currently consulting at one of the top business intelligence consultancies helping clients build data warehouses, data lakes, cloud data processing pipelines and machine learning pipelines. The technologies he uses to accomplish client requirements range from Hadoop, Amazon S3, Python, Django, Apache Spark, MSBI, Microsoft Azure, SQL Server Data Tools, Talend and Elastic MapReduce. Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'677a174ceda00756',m:'2e108b6fd7e4a912abcabe7554382f62f6cef40e-1627768737-1800-AQ+1hRQHAbr8Gk2gAO8mpFOiG0K6YMdeTbDfHod7xqZNM4f9nKHlsiUUy9ByrklWQ5yjM/df5RnGmhXfiKfqkkcm/sTle/nxodaZ9+DX2sPhn08DtpPpMIVPn35a9LILYMrt3jLyUwWW3pn24vElm5amy3VIRQMtqoZ+yEbOCldmoMpOccW5doB6DmTESH8f5g==',s:[0x8168ea8ea7,0x37a5fcbe1c],}})();
  2. R Programming Data Analysis Big Data Machine Learning Geo Mapping with ArcGIS Maps for Power BI Geospatial Machine Learning Creating Dashboards Course content 6 sections • 19 lectures • 2h 26m total length Expand all sections Introduction 1 lecture • 8min Introduction Preview 07:31 Setup and Installations 5 lectures • 31min R Installation Preview 05:10 Installing Apache Spark 12:06 Installing Java (Optional) 04:35 Testing Apache Spark Installation 02:32 Installing Sparklyr 06:31 Building the Big Data ETL Pipeline with Sparklyr 3 lectures • 31min Data Extraction 05:43 Data Transformation 17:35 Data Exporting 07:26 Big Data Machine Learning with Sparklyr 3 lectures • 37min Data Pre-processing 17:34 Building the Predictive Model 09:30 Creating the Prediction Dataset 09:35 Data Visualization with Power BI 6 lectures • 41min Installing Power BI Desktop 01:54 Loading the Data Sources 08:29 Creating a Geo Map 09:22 Creating a Donut Chart 04:53 Create an Area Chart 07:25 Create a Bar Chart 08:58 Project Source Code 1 lecture • 1min Source Code 00:02 Requirements Basic Understanding of R Programming Little or no understanding of GIS Basic understanding of Programming concepts Basic understanding of Data Basic understanding of what Machine Learning is Description Welcome to the Building Big Data Pipelines with R & Sparklyr & PowerBI course. In this course we will be creating a big data analytics solution using big data technologies for R . In our use case we will be working with raw earthquake data, we will be applying big data processing techniques to extract transform and load the data into usable datasets. Once we have processed and cleaned the data, we will use it as a data source for building predictive analytics and visualizations. Power BI Desktop is a powerful data visualization tool that lets you build advanced queries, models and reports. With Power BI Desktop, you can connect to multiple data sources and combine them into a data model. This data model lets you build visuals, and dashboards that you can share as reports with other people in your organization. Sparklyr is an open-source library that is used for processing big data in R , by providing an interface between R and Apache Spark . It allows you to take advantage of Spark's ability to process and analyze large datasets in a distributed and interactive manner. It also provides interfaces to Spark's distributed machine learning algorithms and much more. You will learn how to create big data processing pipelines using R You will learn machine learning with geospatial data using the Sparklyr library You will learn data analysis using Sparklyr, R and Power BI You will learn how to manipulate, clean and transform data using Spark dataframes You will learn how to create Geo Maps in Power BI Desktop You will also learn how to create dashboards in Power BI Desktop Who this course is for: R Developers at any level Data Engineers at any level Developers at any level Machine Learning engineers at any level Data Scientists at any level GIS Developers at any level The curious mind Show more Show less Instructor EBISYS R&D Big Data Engineering 4.2 Instructor Rating 264 Reviews 1,277 Students 13 Courses Big Data Engineering and Consulting, involved in multiple projects ranging from Business Intelligence, Software Engineering, IoT and Big data analytics. Expertise are in building data processing pipelines in the Hadoop and Cloud ecosystems and software development. Currently consulting at one of the top business intelligence consultancies helping clients build data warehouses, data lakes, cloud data processing pipelines and machine learning pipelines. The technologies he uses to accomplish client requirements range from Hadoop, Amazon S3, Python, Django, Apache Spark, MSBI, Microsoft Azure, SQL Server Data Tools, Talend and Elastic MapReduce. Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'677a174ceda00756',m:'2e108b6fd7e4a912abcabe7554382f62f6cef40e-1627768737-1800-AQ+1hRQHAbr8Gk2gAO8mpFOiG0K6YMdeTbDfHod7xqZNM4f9nKHlsiUUy9ByrklWQ5yjM/df5RnGmhXfiKfqkkcm/sTle/nxodaZ9+DX2sPhn08DtpPpMIVPn35a9LILYMrt3jLyUwWW3pn24vElm5amy3VIRQMtqoZ+yEbOCldmoMpOccW5doB6DmTESH8f5g==',s:[0x8168ea8ea7,0x37a5fcbe1c],}})();
  3. Data Analysis Big Data Machine Learning Geo Mapping with ArcGIS Maps for Power BI Geospatial Machine Learning Creating Dashboards Course content 6 sections • 19 lectures • 2h 26m total length Expand all sections Introduction 1 lecture • 8min Introduction Preview 07:31 Setup and Installations 5 lectures • 31min R Installation Preview 05:10 Installing Apache Spark 12:06 Installing Java (Optional) 04:35 Testing Apache Spark Installation 02:32 Installing Sparklyr 06:31 Building the Big Data ETL Pipeline with Sparklyr 3 lectures • 31min Data Extraction 05:43 Data Transformation 17:35 Data Exporting 07:26 Big Data Machine Learning with Sparklyr 3 lectures • 37min Data Pre-processing 17:34 Building the Predictive Model 09:30 Creating the Prediction Dataset 09:35 Data Visualization with Power BI 6 lectures • 41min Installing Power BI Desktop 01:54 Loading the Data Sources 08:29 Creating a Geo Map 09:22 Creating a Donut Chart 04:53 Create an Area Chart 07:25 Create a Bar Chart 08:58 Project Source Code 1 lecture • 1min Source Code 00:02 Requirements Basic Understanding of R Programming Little or no understanding of GIS Basic understanding of Programming concepts Basic understanding of Data Basic understanding of what Machine Learning is Description Welcome to the Building Big Data Pipelines with R & Sparklyr & PowerBI course. In this course we will be creating a big data analytics solution using big data technologies for R . In our use case we will be working with raw earthquake data, we will be applying big data processing techniques to extract transform and load the data into usable datasets. Once we have processed and cleaned the data, we will use it as a data source for building predictive analytics and visualizations. Power BI Desktop is a powerful data visualization tool that lets you build advanced queries, models and reports. With Power BI Desktop, you can connect to multiple data sources and combine them into a data model. This data model lets you build visuals, and dashboards that you can share as reports with other people in your organization. Sparklyr is an open-source library that is used for processing big data in R , by providing an interface between R and Apache Spark . It allows you to take advantage of Spark's ability to process and analyze large datasets in a distributed and interactive manner. It also provides interfaces to Spark's distributed machine learning algorithms and much more. You will learn how to create big data processing pipelines using R You will learn machine learning with geospatial data using the Sparklyr library You will learn data analysis using Sparklyr, R and Power BI You will learn how to manipulate, clean and transform data using Spark dataframes You will learn how to create Geo Maps in Power BI Desktop You will also learn how to create dashboards in Power BI Desktop Who this course is for: R Developers at any level Data Engineers at any level Developers at any level Machine Learning engineers at any level Data Scientists at any level GIS Developers at any level The curious mind Show more Show less Instructor EBISYS R&D Big Data Engineering 4.2 Instructor Rating 264 Reviews 1,277 Students 13 Courses Big Data Engineering and Consulting, involved in multiple projects ranging from Business Intelligence, Software Engineering, IoT and Big data analytics. Expertise are in building data processing pipelines in the Hadoop and Cloud ecosystems and software development. Currently consulting at one of the top business intelligence consultancies helping clients build data warehouses, data lakes, cloud data processing pipelines and machine learning pipelines. The technologies he uses to accomplish client requirements range from Hadoop, Amazon S3, Python, Django, Apache Spark, MSBI, Microsoft Azure, SQL Server Data Tools, Talend and Elastic MapReduce. Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'677a174ceda00756',m:'2e108b6fd7e4a912abcabe7554382f62f6cef40e-1627768737-1800-AQ+1hRQHAbr8Gk2gAO8mpFOiG0K6YMdeTbDfHod7xqZNM4f9nKHlsiUUy9ByrklWQ5yjM/df5RnGmhXfiKfqkkcm/sTle/nxodaZ9+DX2sPhn08DtpPpMIVPn35a9LILYMrt3jLyUwWW3pn24vElm5amy3VIRQMtqoZ+yEbOCldmoMpOccW5doB6DmTESH8f5g==',s:[0x8168ea8ea7,0x37a5fcbe1c],}})();
  4. Big Data Machine Learning Geo Mapping with ArcGIS Maps for Power BI Geospatial Machine Learning Creating Dashboards Course content 6 sections • 19 lectures • 2h 26m total length Expand all sections Introduction 1 lecture • 8min Introduction Preview 07:31 Setup and Installations 5 lectures • 31min R Installation Preview 05:10 Installing Apache Spark 12:06 Installing Java (Optional) 04:35 Testing Apache Spark Installation 02:32 Installing Sparklyr 06:31 Building the Big Data ETL Pipeline with Sparklyr 3 lectures • 31min Data Extraction 05:43 Data Transformation 17:35 Data Exporting 07:26 Big Data Machine Learning with Sparklyr 3 lectures • 37min Data Pre-processing 17:34 Building the Predictive Model 09:30 Creating the Prediction Dataset 09:35 Data Visualization with Power BI 6 lectures • 41min Installing Power BI Desktop 01:54 Loading the Data Sources 08:29 Creating a Geo Map 09:22 Creating a Donut Chart 04:53 Create an Area Chart 07:25 Create a Bar Chart 08:58 Project Source Code 1 lecture • 1min Source Code 00:02 Requirements Basic Understanding of R Programming Little or no understanding of GIS Basic understanding of Programming concepts Basic understanding of Data Basic understanding of what Machine Learning is Description Welcome to the Building Big Data Pipelines with R & Sparklyr & PowerBI course. In this course we will be creating a big data analytics solution using big data technologies for R . In our use case we will be working with raw earthquake data, we will be applying big data processing techniques to extract transform and load the data into usable datasets. Once we have processed and cleaned the data, we will use it as a data source for building predictive analytics and visualizations. Power BI Desktop is a powerful data visualization tool that lets you build advanced queries, models and reports. With Power BI Desktop, you can connect to multiple data sources and combine them into a data model. This data model lets you build visuals, and dashboards that you can share as reports with other people in your organization. Sparklyr is an open-source library that is used for processing big data in R , by providing an interface between R and Apache Spark . It allows you to take advantage of Spark's ability to process and analyze large datasets in a distributed and interactive manner. It also provides interfaces to Spark's distributed machine learning algorithms and much more. You will learn how to create big data processing pipelines using R You will learn machine learning with geospatial data using the Sparklyr library You will learn data analysis using Sparklyr, R and Power BI You will learn how to manipulate, clean and transform data using Spark dataframes You will learn how to create Geo Maps in Power BI Desktop You will also learn how to create dashboards in Power BI Desktop Who this course is for: R Developers at any level Data Engineers at any level Developers at any level Machine Learning engineers at any level Data Scientists at any level GIS Developers at any level The curious mind Show more Show less Instructor EBISYS R&D Big Data Engineering 4.2 Instructor Rating 264 Reviews 1,277 Students 13 Courses Big Data Engineering and Consulting, involved in multiple projects ranging from Business Intelligence, Software Engineering, IoT and Big data analytics. Expertise are in building data processing pipelines in the Hadoop and Cloud ecosystems and software development. Currently consulting at one of the top business intelligence consultancies helping clients build data warehouses, data lakes, cloud data processing pipelines and machine learning pipelines. The technologies he uses to accomplish client requirements range from Hadoop, Amazon S3, Python, Django, Apache Spark, MSBI, Microsoft Azure, SQL Server Data Tools, Talend and Elastic MapReduce. Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'677a174ceda00756',m:'2e108b6fd7e4a912abcabe7554382f62f6cef40e-1627768737-1800-AQ+1hRQHAbr8Gk2gAO8mpFOiG0K6YMdeTbDfHod7xqZNM4f9nKHlsiUUy9ByrklWQ5yjM/df5RnGmhXfiKfqkkcm/sTle/nxodaZ9+DX2sPhn08DtpPpMIVPn35a9LILYMrt3jLyUwWW3pn24vElm5amy3VIRQMtqoZ+yEbOCldmoMpOccW5doB6DmTESH8f5g==',s:[0x8168ea8ea7,0x37a5fcbe1c],}})();
  5. Geo Mapping with ArcGIS Maps for Power BI Geospatial Machine Learning Creating Dashboards Course content 6 sections • 19 lectures • 2h 26m total length Expand all sections Introduction 1 lecture • 8min Introduction Preview 07:31 Setup and Installations 5 lectures • 31min R Installation Preview 05:10 Installing Apache Spark 12:06 Installing Java (Optional) 04:35 Testing Apache Spark Installation 02:32 Installing Sparklyr 06:31 Building the Big Data ETL Pipeline with Sparklyr 3 lectures • 31min Data Extraction 05:43 Data Transformation 17:35 Data Exporting 07:26 Big Data Machine Learning with Sparklyr 3 lectures • 37min Data Pre-processing 17:34 Building the Predictive Model 09:30 Creating the Prediction Dataset 09:35 Data Visualization with Power BI 6 lectures • 41min Installing Power BI Desktop 01:54 Loading the Data Sources 08:29 Creating a Geo Map 09:22 Creating a Donut Chart 04:53 Create an Area Chart 07:25 Create a Bar Chart 08:58 Project Source Code 1 lecture • 1min Source Code 00:02 Requirements Basic Understanding of R Programming Little or no understanding of GIS Basic understanding of Programming concepts Basic understanding of Data Basic understanding of what Machine Learning is Description Welcome to the Building Big Data Pipelines with R & Sparklyr & PowerBI course. In this course we will be creating a big data analytics solution using big data technologies for R . In our use case we will be working with raw earthquake data, we will be applying big data processing techniques to extract transform and load the data into usable datasets. Once we have processed and cleaned the data, we will use it as a data source for building predictive analytics and visualizations. Power BI Desktop is a powerful data visualization tool that lets you build advanced queries, models and reports. With Power BI Desktop, you can connect to multiple data sources and combine them into a data model. This data model lets you build visuals, and dashboards that you can share as reports with other people in your organization. Sparklyr is an open-source library that is used for processing big data in R , by providing an interface between R and Apache Spark . It allows you to take advantage of Spark's ability to process and analyze large datasets in a distributed and interactive manner. It also provides interfaces to Spark's distributed machine learning algorithms and much more. You will learn how to create big data processing pipelines using R You will learn machine learning with geospatial data using the Sparklyr library You will learn data analysis using Sparklyr, R and Power BI You will learn how to manipulate, clean and transform data using Spark dataframes You will learn how to create Geo Maps in Power BI Desktop You will also learn how to create dashboards in Power BI Desktop Who this course is for: R Developers at any level Data Engineers at any level Developers at any level Machine Learning engineers at any level Data Scientists at any level GIS Developers at any level The curious mind Show more Show less Instructor EBISYS R&D Big Data Engineering 4.2 Instructor Rating 264 Reviews 1,277 Students 13 Courses Big Data Engineering and Consulting, involved in multiple projects ranging from Business Intelligence, Software Engineering, IoT and Big data analytics. Expertise are in building data processing pipelines in the Hadoop and Cloud ecosystems and software development. Currently consulting at one of the top business intelligence consultancies helping clients build data warehouses, data lakes, cloud data processing pipelines and machine learning pipelines. The technologies he uses to accomplish client requirements range from Hadoop, Amazon S3, Python, Django, Apache Spark, MSBI, Microsoft Azure, SQL Server Data Tools, Talend and Elastic MapReduce. Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'677a174ceda00756',m:'2e108b6fd7e4a912abcabe7554382f62f6cef40e-1627768737-1800-AQ+1hRQHAbr8Gk2gAO8mpFOiG0K6YMdeTbDfHod7xqZNM4f9nKHlsiUUy9ByrklWQ5yjM/df5RnGmhXfiKfqkkcm/sTle/nxodaZ9+DX2sPhn08DtpPpMIVPn35a9LILYMrt3jLyUwWW3pn24vElm5amy3VIRQMtqoZ+yEbOCldmoMpOccW5doB6DmTESH8f5g==',s:[0x8168ea8ea7,0x37a5fcbe1c],}})();
  6. Geospatial Machine Learning Creating Dashboards Course content 6 sections • 19 lectures • 2h 26m total length Expand all sections Introduction 1 lecture • 8min Introduction Preview 07:31 Setup and Installations 5 lectures • 31min R Installation Preview 05:10 Installing Apache Spark 12:06 Installing Java (Optional) 04:35 Testing Apache Spark Installation 02:32 Installing Sparklyr 06:31 Building the Big Data ETL Pipeline with Sparklyr 3 lectures • 31min Data Extraction 05:43 Data Transformation 17:35 Data Exporting 07:26 Big Data Machine Learning with Sparklyr 3 lectures • 37min Data Pre-processing 17:34 Building the Predictive Model 09:30 Creating the Prediction Dataset 09:35 Data Visualization with Power BI 6 lectures • 41min Installing Power BI Desktop 01:54 Loading the Data Sources 08:29 Creating a Geo Map 09:22 Creating a Donut Chart 04:53 Create an Area Chart 07:25 Create a Bar Chart 08:58 Project Source Code 1 lecture • 1min Source Code 00:02 Requirements Basic Understanding of R Programming Little or no understanding of GIS Basic understanding of Programming concepts Basic understanding of Data Basic understanding of what Machine Learning is Description Welcome to the Building Big Data Pipelines with R & Sparklyr & PowerBI course. In this course we will be creating a big data analytics solution using big data technologies for R . In our use case we will be working with raw earthquake data, we will be applying big data processing techniques to extract transform and load the data into usable datasets. Once we have processed and cleaned the data, we will use it as a data source for building predictive analytics and visualizations. Power BI Desktop is a powerful data visualization tool that lets you build advanced queries, models and reports. With Power BI Desktop, you can connect to multiple data sources and combine them into a data model. This data model lets you build visuals, and dashboards that you can share as reports with other people in your organization. Sparklyr is an open-source library that is used for processing big data in R , by providing an interface between R and Apache Spark . It allows you to take advantage of Spark's ability to process and analyze large datasets in a distributed and interactive manner. It also provides interfaces to Spark's distributed machine learning algorithms and much more. You will learn how to create big data processing pipelines using R You will learn machine learning with geospatial data using the Sparklyr library You will learn data analysis using Sparklyr, R and Power BI You will learn how to manipulate, clean and transform data using Spark dataframes You will learn how to create Geo Maps in Power BI Desktop You will also learn how to create dashboards in Power BI Desktop Who this course is for: R Developers at any level Data Engineers at any level Developers at any level Machine Learning engineers at any level Data Scientists at any level GIS Developers at any level The curious mind Show more Show less Instructor EBISYS R&D Big Data Engineering 4.2 Instructor Rating 264 Reviews 1,277 Students 13 Courses Big Data Engineering and Consulting, involved in multiple projects ranging from Business Intelligence, Software Engineering, IoT and Big data analytics. Expertise are in building data processing pipelines in the Hadoop and Cloud ecosystems and software development. Currently consulting at one of the top business intelligence consultancies helping clients build data warehouses, data lakes, cloud data processing pipelines and machine learning pipelines. The technologies he uses to accomplish client requirements range from Hadoop, Amazon S3, Python, Django, Apache Spark, MSBI, Microsoft Azure, SQL Server Data Tools, Talend and Elastic MapReduce. Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'677a174ceda00756',m:'2e108b6fd7e4a912abcabe7554382f62f6cef40e-1627768737-1800-AQ+1hRQHAbr8Gk2gAO8mpFOiG0K6YMdeTbDfHod7xqZNM4f9nKHlsiUUy9ByrklWQ5yjM/df5RnGmhXfiKfqkkcm/sTle/nxodaZ9+DX2sPhn08DtpPpMIVPn35a9LILYMrt3jLyUwWW3pn24vElm5amy3VIRQMtqoZ+yEbOCldmoMpOccW5doB6DmTESH8f5g==',s:[0x8168ea8ea7,0x37a5fcbe1c],}})();
  7. Creating Dashboards Course content 6 sections • 19 lectures • 2h 26m total length Expand all sections Introduction 1 lecture • 8min Introduction Preview 07:31 Setup and Installations 5 lectures • 31min R Installation Preview 05:10 Installing Apache Spark 12:06 Installing Java (Optional) 04:35 Testing Apache Spark Installation 02:32 Installing Sparklyr 06:31 Building the Big Data ETL Pipeline with Sparklyr 3 lectures • 31min Data Extraction 05:43 Data Transformation 17:35 Data Exporting 07:26 Big Data Machine Learning with Sparklyr 3 lectures • 37min Data Pre-processing 17:34 Building the Predictive Model 09:30 Creating the Prediction Dataset 09:35 Data Visualization with Power BI 6 lectures • 41min Installing Power BI Desktop 01:54 Loading the Data Sources 08:29 Creating a Geo Map 09:22 Creating a Donut Chart 04:53 Create an Area Chart 07:25 Create a Bar Chart 08:58 Project Source Code 1 lecture • 1min Source Code 00:02 Requirements Basic Understanding of R Programming Little or no understanding of GIS Basic understanding of Programming concepts Basic understanding of Data Basic understanding of what Machine Learning is Description Welcome to the Building Big Data Pipelines with R & Sparklyr & PowerBI course. In this course we will be creating a big data analytics solution using big data technologies for R . In our use case we will be working with raw earthquake data, we will be applying big data processing techniques to extract transform and load the data into usable datasets. Once we have processed and cleaned the data, we will use it as a data source for building predictive analytics and visualizations. Power BI Desktop is a powerful data visualization tool that lets you build advanced queries, models and reports. With Power BI Desktop, you can connect to multiple data sources and combine them into a data model. This data model lets you build visuals, and dashboards that you can share as reports with other people in your organization. Sparklyr is an open-source library that is used for processing big data in R , by providing an interface between R and Apache Spark . It allows you to take advantage of Spark's ability to process and analyze large datasets in a distributed and interactive manner. It also provides interfaces to Spark's distributed machine learning algorithms and much more. You will learn how to create big data processing pipelines using R You will learn machine learning with geospatial data using the Sparklyr library You will learn data analysis using Sparklyr, R and Power BI You will learn how to manipulate, clean and transform data using Spark dataframes You will learn how to create Geo Maps in Power BI Desktop You will also learn how to create dashboards in Power BI Desktop Who this course is for: R Developers at any level Data Engineers at any level Developers at any level Machine Learning engineers at any level Data Scientists at any level GIS Developers at any level The curious mind Show more Show less Instructor EBISYS R&D Big Data Engineering 4.2 Instructor Rating 264 Reviews 1,277 Students 13 Courses Big Data Engineering and Consulting, involved in multiple projects ranging from Business Intelligence, Software Engineering, IoT and Big data analytics. Expertise are in building data processing pipelines in the Hadoop and Cloud ecosystems and software development. Currently consulting at one of the top business intelligence consultancies helping clients build data warehouses, data lakes, cloud data processing pipelines and machine learning pipelines. The technologies he uses to accomplish client requirements range from Hadoop, Amazon S3, Python, Django, Apache Spark, MSBI, Microsoft Azure, SQL Server Data Tools, Talend and Elastic MapReduce. Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'677a174ceda00756',m:'2e108b6fd7e4a912abcabe7554382f62f6cef40e-1627768737-1800-AQ+1hRQHAbr8Gk2gAO8mpFOiG0K6YMdeTbDfHod7xqZNM4f9nKHlsiUUy9ByrklWQ5yjM/df5RnGmhXfiKfqkkcm/sTle/nxodaZ9+DX2sPhn08DtpPpMIVPn35a9LILYMrt3jLyUwWW3pn24vElm5amy3VIRQMtqoZ+yEbOCldmoMpOccW5doB6DmTESH8f5g==',s:[0x8168ea8ea7,0x37a5fcbe1c],}})();