{"id":44057,"date":"2025-07-14T22:38:40","date_gmt":"2025-07-14T17:38:40","guid":{"rendered":"https:\/\/chartexpo.com\/blog\/?p=44057"},"modified":"2025-09-25T15:33:05","modified_gmt":"2025-09-25T10:33:05","slug":"what-are-data-pipelines","status":"publish","type":"post","link":"https:\/\/chartexpo.com\/blog\/what-are-data-pipelines","title":{"rendered":"What are Data Pipelines and How They Support Insights?"},"content":{"rendered":"<p>Her data pipeline explained how data helps organizations make informed decisions, enhances operational efficiency, fosters innovation, and supports strategic planning. It also drives growth and competitive advantage in the business environment.<\/p>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" style=\"max-width: 100%;\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/what-are-data-pipelines.jpg\" alt=\"What are Data Pipelines\" \/><\/a><\/div>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/utmAction\/MTYrYmxvZytwYitjZXhwbytQQkk2ODgrU2Fua2V5Kw==\" target=\"_blank\" rel=\"noopener noreferrer nofollow\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2023\/04\/CTA-in-power-bi.jpg\" alt=\"\" width=\"205\" height=\"113\" \/><\/a> <a href=\"https:\/\/chartexpo.com\/utmAction\/MTYrYmxvZytncytjZXhwbytDRTY4OCs=\" target=\"_blank\" rel=\"noopener noreferrer nofollow\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2023\/04\/CTA-in-google-sheets.jpg\" alt=\"\" width=\"205\" height=\"113\" \/><\/a> <a href=\"https:\/\/chartexpo.com\/TrafficTracker\/MTYrYmxvZytzZStjZXhwbytDRTY4OCs=\" target=\"_blank\" rel=\"noopener noreferrer nofollow\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2023\/04\/CTA-in-microsoft-excel.jpg\" alt=\"\" width=\"205\" height=\"113\" \/><\/a><\/div>\n<p>But what are data pipeline basics? Well, this guide shows you what data pipeline meaning are, the importance of data pipelines, and how to build data pipelines.<\/p>\n<h3>Table of Content:<\/h3>\n<ol>\n<li><a href=\"#what-is-a-data-pipeline\">What is a Data Pipeline?<\/a><\/li>\n<li><a href=\"#why-building-data-pipelines-important\">Why are Building Data Pipelines Important?<\/a><\/li>\n<li><a href=\"#data-pipeline-examples-explained\">Explain Data Pipeline Examples<\/a><\/li>\n<li><a href=\"#different-types-of-data-pipelines\">What are Different Types of Data Pipelines?<\/a><\/li>\n<li><a href=\"#data-pipeline-architecture-explained\">What Is a Data Pipeline Architecture?<\/a><\/li>\n<li><a href=\"#how-data-pipelines-work\">How Data Pipelines Work?<\/a><\/li>\n<li><a href=\"#data-pipeline-tools\">What are Data Pipeline Tools?<\/a><\/li>\n<li><a href=\"#how-to-create-a-data-pipeline\">How to Create a Data Pipeline?<\/a>\n<ul>\n<li><a href=\"#identify-your-data-sources-data-pipeline\">Step 1: Identify Your Data Sources<\/a><\/li>\n<li><a href=\"#define-data-requirements-pipeline\">Step 2: Define Data Requirements<\/a><\/li>\n<li><a href=\"#design-data-transformations-pipeline\">Step 3: Design Data Transformations<\/a><\/li>\n<li><a href=\"#choose-your-destination-pipeline\">Step 4: Choose Your Destination<\/a><\/li>\n<li><a href=\"#set-up-orchestration-data-pipeline\">Step 5: Set Up Orchestration<\/a><\/li>\n<li><a href=\"#implement-monitoring-data-pipeline\">Step 6: Implement Monitoring<\/a><\/li>\n<li><a href=\"#test-and-optimize-data-pipeline\">Step 7: Test and Optimize<\/a><\/li>\n<\/ul>\n<\/li>\n<li><a href=\"#create-data-pipeline-visualization-power-bi\">How to Create Data Pipeline Visualization\u00a0in Power BI?<\/a><\/li>\n<li><a href=\"#data-pipeline-vs-etl-pipeline\">What is the Difference Between Data pipeline vs. ETL pipeline?<\/a><\/li>\n<li><a href=\"#advantages-of-data-pipeline\">What are the Advantages of Data Pipeline?<\/a><\/li>\n<li><a href=\"#challenges-in-building-data-pipelines\">What are Challenges for Building Data Pipelines?<\/a><\/li>\n<li><a href=\"#tips-for-effective-data-processing-pipeline\">Tips for an Effective Data Processing Pipeline<\/a><\/li>\n<li><a href=\"#top-5-use-cases-of-data-pipelines\">Top 5 Use Cases of Data Pipelines<\/a><\/li>\n<li><a href=\"#future-of-data-pipelines\">What is the future of Data Pipelines?<\/a><\/li>\n<li><a href=\"#data-pipelines-faqs\">Data Pipelines &#8211; FAQs<\/a><\/li>\n<li><a href=\"#wrap-up\">Wrap Up<\/a><\/li>\n<\/ol>\n<p>First&#8230;<\/p>\n<h2 id=\"what-is-a-data-pipeline\">What is a Data Pipeline?<\/h2>\n<p><strong>Definition: <\/strong>A data pipeline is a set of automated processes that collects, moves, and transforms data from different sources to a destination where it can be stored, analyzed, and used for decision-making.<\/p>\n<p>Think of it as a system that ensures your data flows smoothly and accurately, cleaning and organizing it along the way so it\u2019s ready for reporting, analytics, or feeding into business tools. By automating these steps, a data pipeline means is that help organizations save time, maintain data quality, and make insights available faster for smarter decisions.<\/p>\n<h3>Key Components of Data Pipelines:<\/h3>\n<ul>\n<li data-start=\"114\" data-end=\"305\"><strong data-start=\"114\" data-end=\"126\">Sources:<\/strong> These are the starting points where data is collected, including databases, cloud services, applications, and APIs. They provide the raw data that will flow through the pipeline.<\/li>\n<li data-start=\"309\" data-end=\"561\"><strong data-start=\"309\" data-end=\"329\">Transformations:<\/strong> This stage involves cleaning, filtering, and restructuring data to ensure it is accurate, consistent, and ready for analysis. It may include removing duplicates, converting data types, or enriching data with additional information.<\/li>\n<li data-start=\"565\" data-end=\"780\"><strong data-start=\"565\" data-end=\"582\">Destinations:<\/strong> The final location where processed data is stored for analysis and reporting. This could be a data warehouse, <a href=\"https:\/\/chartexpo.com\/blog\/what-is-a-data-lake\" target=\"_blank\" rel=\"noopener\">data lake<\/a>, or a business intelligence platform where teams can access and use the data.<\/li>\n<li data-start=\"784\" data-end=\"949\"><strong data-start=\"784\" data-end=\"802\">Orchestration:<\/strong> This manages and schedules the flow of data through the pipeline, ensuring tasks run in the correct order and handling dependencies between steps.<\/li>\n<li data-start=\"953\" data-end=\"1144\"><strong data-start=\"953\" data-end=\"968\">Monitoring:<\/strong> A crucial component that tracks the health and performance of the pipeline, identifying issues like delays, failures, or data inconsistencies to ensure reliable data delivery.<\/li>\n<\/ul>\n<h2>Video Tutorial: How to Visualize Data Pipelines in Power BI<\/h2>\n<p><iframe title=\"YouTube video player\" src=\"https:\/\/www.youtube.com\/embed\/_UyS9hzktr8?si=zkl8vEiizt8_NipC\" width=\"650\" height=\"365\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\" data-mce-fragment=\"1\"><span data-mce-type=\"bookmark\" style=\"display: inline-block; width: 0px; overflow: hidden; line-height: 0;\" class=\"mce_SELRES_start\">\ufeff<\/span><\/iframe><\/p>\n<h2 id=\"why-building-data-pipelines-important\">Why are Building Data Pipelines Important?<\/h2>\n<ul>\n<li>\n<h3>The Imperative for Real-Time Data Access<\/h3>\n<\/li>\n<\/ul>\n<p>Nowadays, businesses need real-time data access. With a data pipeline, you\u2019ll get a continuous data flow, which can be visualized using <a href=\"https:\/\/chartexpo.com\/blog\/data-flow-diagram\" target=\"_blank\" rel=\"noopener\">data flow diagrams<\/a>, helping companies react to market changes and make informed decisions.<\/p>\n<ul>\n<li>\n<h3>Upholding Data Quality and Integrity<\/h3>\n<\/li>\n<\/ul>\n<p>Data is as good as its quality and integrity. With a data pipeline, you&#8217;ll have clean, consistent, and reliable data. It automates the process of correcting and detecting errors, and that helps maintain the integrity of the data. It also keeps business owners from making misguided decisions.<\/p>\n<ul>\n<li>\n<h3>Enhancing Analytical Capabilities<\/h3>\n<\/li>\n<\/ul>\n<p>Insights obtained from <a href=\"https:\/\/chartexpo.com\/blog\/data-analysis\" target=\"_blank\" rel=\"noopener\">data analysis<\/a> are timely and accurate as the data feeds into the analytical tools. Data pipelines automate data preparation and delivery to these tools, and that ensures that insights generated are based on the most current and well-processed data available.<\/p>\n<ul>\n<li>\n<h3>Streaming Data Pipeline<\/h3>\n<\/li>\n<\/ul>\n<p>With a data pipeline, businesses are sure to meet the regulatory standards in their region. Data pipelines also provide a clear and controlled data flow with audit trails and governance controls.<\/p>\n<h2 id=\"data-pipeline-examples-explained\">Explain Data Pipeline Examples<\/h2>\n<ul>\n<li data-start=\"129\" data-end=\"164\">\n<h3>ETL Pipeline for Sales Data<\/h3>\n<\/li>\n<\/ul>\n<p data-start=\"165\" data-end=\"375\">A retail company extracts sales data from its POS systems (Extract), cleans and formats the data (Transform), and loads it into a <a href=\"https:\/\/chartexpo.com\/blog\/cloud-based-data-warehouse\" target=\"_blank\" rel=\"noopener\">data warehouse<\/a> like BigQuery (Load) for weekly sales analysis and reporting.<\/p>\n<ul>\n<li data-start=\"382\" data-end=\"421\">\n<h3>Real-Time Clickstream Analytics<\/h3>\n<\/li>\n<\/ul>\n<p data-start=\"422\" data-end=\"653\">An e-commerce site captures user clickstream data in real time, streams it through tools like Apache Kafka, and processes it using Spark Streaming to analyze user behavior instantly for personalized product recommendations.<\/p>\n<ul>\n<li data-start=\"660\" data-end=\"692\">\n<h3>IoT Sensor Data Pipeline<\/h3>\n<\/li>\n<\/ul>\n<p data-start=\"693\" data-end=\"902\">A manufacturing company collects temperature and vibration data from IoT sensors, processes it in real-time, and stores it in a time-series database to monitor machine health and predict maintenance needs.<\/p>\n<ul>\n<li data-start=\"909\" data-end=\"957\">\n<h3>Social Media Sentiment Analysis Pipeline<\/h3>\n<\/li>\n<\/ul>\n<p data-start=\"958\" data-end=\"1157\">A marketing team uses a pipeline to extract tweets mentioning their brand, process text for sentiment analysis, and visualize trends in dashboards to track public perception and adjust campaigns.<\/p>\n<h2 id=\"different-types-of-data-pipelines\">What are Different Types of Data Pipelines?<\/h2>\n<ul>\n<li data-start=\"165\" data-end=\"193\">\n<h3><strong>Batch Data Pipelines<\/strong><\/h3>\n<\/li>\n<\/ul>\n<p data-start=\"194\" data-end=\"430\">These pipelines collect and process data in chunks at scheduled intervals (daily, hourly, or weekly). They are ideal for situations where real-time analysis isn\u2019t critical, such as generating daily sales reports or data backups.<\/p>\n<p data-start=\"432\" data-end=\"517\"><strong data-start=\"432\" data-end=\"444\">Example:<\/strong> Importing CSV sales data into a data warehouse every night for analysis.<\/p>\n<ul>\n<li data-start=\"524\" data-end=\"568\">\n<h3><strong>Real-Time (Streaming) Data Pipelines<\/strong><\/h3>\n<\/li>\n<\/ul>\n<p data-start=\"68\" data-end=\"330\">These pipelines handle data the moment it\u2019s created, allowing for instant analysis and quick decision-making. They\u2019re ideal for situations like fraud detection, real-time user tracking, or IoT monitoring, where having immediate insights makes all the difference.<\/p>\n<p data-start=\"796\" data-end=\"890\"><strong data-start=\"796\" data-end=\"808\">Example:<\/strong> Monitoring credit card transactions in real time to detect suspicious activities.<\/p>\n<ul>\n<li data-start=\"897\" data-end=\"932\">\n<h3><strong>Cloud-Native Data Pipelines<\/strong><\/h3>\n<\/li>\n<\/ul>\n<p data-start=\"933\" data-end=\"1193\">These pipelines are designed to run fully in cloud environments, automatically scaling with data volume and providing flexibility for modern data needs. They support both batch and real-time processing while reducing infrastructure management overhead.<\/p>\n<p data-start=\"1195\" data-end=\"1337\"><strong data-start=\"1195\" data-end=\"1207\">Example:<\/strong> Using Google Cloud Dataflow or AWS Glue to handle data movement and transformation across your cloud storage and analytics tools.<\/p>\n<h2 id=\"data-pipeline-architecture-explained\">What Is a Data Pipeline Architecture?<\/h2>\n<p data-start=\"105\" data-end=\"292\">Data pipeline architecture refers to the structured design of how data moves from its source to its final destination for analysis or storage. It typically includes three core stages:<\/p>\n<ol>\n<li data-start=\"297\" data-end=\"550\"><strong data-start=\"297\" data-end=\"316\">Data Ingestion: <\/strong>Gathering data from multiple sources, including SaaS tools, IoT devices, and databases, in both structured and unstructured forms. This step often includes initial validations to ensure data consistency before moving to processing.<\/li>\n<li data-start=\"555\" data-end=\"810\"><strong data-start=\"555\" data-end=\"579\">Data Transformation:<\/strong> Cleaning, enriching, and converting raw data into a usable format using automated processes. This can include flattening nested data, filtering unnecessary information, and applying business rules to prepare the data for analysis.<\/li>\n<li data-start=\"815\" data-end=\"997\"><strong data-start=\"815\" data-end=\"832\">Data Storage:<\/strong> Storing the transformed data in a data warehouse, data lake, or other repositories where it is accessible for reporting, analytics, and <a href=\"https:\/\/chartexpo.com\/blog\/best-business-intelligence-platform\" target=\"_blank\" rel=\"noopener\">business intelligence tools<\/a>.<\/li>\n<\/ol>\n<h2 id=\"how-data-pipelines-work\">How Data Pipelines Work?<\/h2>\n<p data-start=\"110\" data-end=\"267\">Data pipelines work by collecting data from multiple sources, transforming it for consistency, and sending it to storage or analytics tools for insights.<\/p>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2025\/07\/Data-Piplines.png\"><img decoding=\"async\" class=\"alignnone size full wp image 4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2025\/07\/Data-Piplines.png\" alt=\"Data Piplines Working\" width=\"650\" \/><\/a><\/div>\n<p data-start=\"269\" data-end=\"291\">As shown in the image:<\/p>\n<ul>\n<li data-start=\"295\" data-end=\"409\"><strong data-start=\"295\" data-end=\"312\">Data Sources:<\/strong> Infrastructure logs, application logs, and SaaS metrics enter the pipeline as raw data events.<\/li>\n<li data-start=\"412\" data-end=\"554\"><strong data-start=\"412\" data-end=\"427\">Processing:<\/strong> Inside the pipeline, these events are organized into metrics, logs, and archival data for structured processing.<\/li>\n<li data-start=\"557\" data-end=\"629\"><strong data-start=\"557\" data-end=\"568\">Output:<\/strong> Finally, the processed data flows to different destinations:\n<ul>\n<li data-start=\"635\" data-end=\"690\">Time series databases for continuous metrics monitoring<\/li>\n<li data-start=\"696\" data-end=\"741\">Indexed storage for easy search and retrieval<\/li>\n<li data-start=\"747\" data-end=\"797\">Direct data stores for deep analysis and reporting<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h2 id=\"data-pipeline-tools\">What are Data Pipeline Tools?<\/h2>\n<p data-start=\"138\" data-end=\"241\">Here are four reliable data pipeline tools to help automate, manage, and scale your data workflows:<\/p>\n<ul>\n<li data-start=\"245\" data-end=\"433\">\n<h3>Apache Airflow<\/h3>\n<\/li>\n<\/ul>\n<p data-start=\"245\" data-end=\"433\">An open-source workflow management tool for orchestrating and scheduling pipelines, making it easier to manage complex <a href=\"https:\/\/chartexpo.com\/blog\/what-is-extraction-transformation-and-loading\" target=\"_blank\" rel=\"noopener\">ETL processes<\/a> visually and systematically.<\/p>\n<ul>\n<li data-start=\"437\" data-end=\"613\">\n<h3>AWS Glue<\/h3>\n<\/li>\n<\/ul>\n<p data-start=\"437\" data-end=\"613\">A serverless ETL service that automates data discovery, preparation, and transformation, integrating seamlessly with AWS data lakes and analytics services.<\/p>\n<ul>\n<li data-start=\"617\" data-end=\"811\">\n<h3>Fivetran<\/h3>\n<\/li>\n<\/ul>\n<p data-start=\"617\" data-end=\"811\">A fully managed pipeline tool that automates data extraction and loading from multiple sources into your data warehouse with minimal setup, ensuring your data stays updated.<\/p>\n<ul>\n<li data-start=\"815\" data-end=\"1075\">\n<h3>Power BI<\/h3>\n<\/li>\n<\/ul>\n<p data-start=\"815\" data-end=\"1075\">While known for data visualization, Power BI also supports <a href=\"https:\/\/chartexpo.com\/blog\/power-bi-deployment-pipelines\" target=\"_blank\" rel=\"noopener\">deployment pipeline<\/a> basics functionalities, allowing you to connect to various data sources, perform <a href=\"https:\/\/chartexpo.com\/blog\/power-bi-transform-data\" target=\"_blank\" rel=\"noopener\">data transformations<\/a> using Power Query, and automate data refreshes for continuous insights.<\/p>\n<h2 id=\"how-to-create-a-data-pipeline\">How to Create a Data Pipeline?<\/h2>\n<ul>\n<li data-start=\"111\" data-end=\"316\">\n<h3 id=\"identify-your-data-sources-data-pipeline\">Step 1: Identify Your Data Sources<\/h3>\n<\/li>\n<\/ul>\n<p data-start=\"111\" data-end=\"316\">Decide where your data will come from, such as databases, cloud storage, APIs, or flat files. This ensures you know what data you need to collect for your pipeline.<\/p>\n<ul>\n<li data-start=\"318\" data-end=\"497\">\n<h3 id=\"define-data-requirements-pipeline\">Step 2: Define Data Requirements<\/h3>\n<\/li>\n<\/ul>\n<p data-start=\"318\" data-end=\"497\">Clarify what data you need, the formats, and the frequency of data collection. This helps in planning how to process and structure the data.<\/p>\n<ul>\n<li data-start=\"499\" data-end=\"717\">\n<h3 id=\"design-data-transformations-pipeline\">Step 3: Design Data Transformations<\/h3>\n<\/li>\n<\/ul>\n<p data-start=\"499\" data-end=\"717\">Plan how you will clean, filter, and structure the data to make it usable for analysis. This could include removing duplicates, handling missing values, and converting formats.<\/p>\n<ul>\n<li data-start=\"719\" data-end=\"922\">\n<h3 id=\"choose-your-destination-pipeline\">Step 4: Choose Your Destination<\/h3>\n<\/li>\n<\/ul>\n<p data-start=\"719\" data-end=\"922\">Select where the processed data will be stored, such as a data warehouse, data lake, or an analytics tool, ensuring it aligns with your analysis and reporting needs.<\/p>\n<ul>\n<li data-start=\"924\" data-end=\"1100\">\n<h3 id=\"set-up-orchestration-data-pipeline\">Step 5: Set Up Orchestration<\/h3>\n<\/li>\n<\/ul>\n<p data-start=\"924\" data-end=\"1100\">Use scheduling tools or pipeline orchestration frameworks to automate and manage the data flow, ensuring each step runs in the correct order.<\/p>\n<ul>\n<li data-start=\"1102\" data-end=\"1301\">\n<h3 id=\"implement-monitoring-data-pipeline\">Step 6: Implement Monitoring<\/h3>\n<\/li>\n<\/ul>\n<p data-start=\"1102\" data-end=\"1301\">Establish monitoring to track the pipeline\u2019s performance and catch issues like failures or delays. This ensures your pipeline delivers reliable and consistent data.<\/p>\n<ul>\n<li data-start=\"1303\" data-end=\"1532\">\n<h3 id=\"test-and-optimize-data-pipeline\">Step 7: Test and Optimize<\/h3>\n<\/li>\n<\/ul>\n<p data-start=\"1303\" data-end=\"1532\">Run tests to ensure the pipeline is working correctly, data is processed accurately, and performance is efficient. Continuously optimize to handle increasing data loads and evolving business needs.<\/p>\n<h2 id=\"create-data-pipeline-visualization-power-bi\">How to Create Data Pipeline Visualization\u00a0in Power BI?<\/h2>\n<h3>Stage 1: Log into Power BI, enter your email, and click \u201cSubmit.\u201d<\/h3>\n<ul>\n<li>Log in to Power BI.<\/li>\n<li>Enter your email address and click the \u201c<strong>Submit<\/strong>\u201d button.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2023\/05\/enter-email-to-login-to-power-bi.jpg\"><img decoding=\"async\" class=\"alignnone size full wp image 4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2023\/05\/enter-email-to-login-to-power-bi.jpg\" alt=\"Enter email to login to Power BI\" width=\"650\" \/><\/a><\/div>\n<ul>\n<li>You are redirected to your Microsoft account.<\/li>\n<li>Enter your password and click \u201c<strong>Sign in<\/strong>\u201c.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2023\/05\/enter-password-to-login-to-power-bi.jpg\"><img decoding=\"async\" class=\"alignnone size full wp image 4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2023\/05\/enter-password-to-login-to-power-bi.jpg\" alt=\"Enter Password to login to Power BI\" width=\"363\" \/><\/a><\/div>\n<ul>\n<li>You can choose whether to stay signed in.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2023\/05\/click-on-stay-signed-in.jpg\"><img decoding=\"async\" class=\"alignnone size full wp image 4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2023\/05\/click-on-stay-signed-in.jpg\" alt=\"Click on stay signed in\" width=\"392\" \/><\/a><\/div>\n<ul>\n<li>Once done, the Power BI home screen will open.<\/li>\n<\/ul>\n<h3>Stage 2: Create a Data Set and Select the Data Set to Use in the Sankey Chart<\/h3>\n<ul>\n<li>Go to the left-side menu and click the \u201c<strong>Create<\/strong>\u201d button.<\/li>\n<li>Select \u201c<strong>Paste or manually enter data<\/strong>\u201c.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/02\/select-paste-or-manually-enter-data-in-power-bi-ce487.jpg\"><img decoding=\"async\" class=\"alignnone size full wp image 4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/02\/select-paste-or-manually-enter-data-in-power-bi-ce487.jpg\" alt=\"select Paste or manually enter data in Power BI ce487\" width=\"650\" \/><\/a><\/div>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/utmAction\/MTYrYmxvZytwYitjZXhwbytQQkk2ODgrU2Fua2V5Kw==\" target=\"_blank\" rel=\"noopener noreferrer nofollow\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2023\/04\/CTA-in-power-bi.jpg\" alt=\"\" width=\"205\" height=\"113\" \/><\/a> <a href=\"https:\/\/chartexpo.com\/utmAction\/MTYrYmxvZytncytjZXhwbytDRTY4OCs=\" target=\"_blank\" rel=\"noopener noreferrer nofollow\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2023\/04\/CTA-in-google-sheets.jpg\" alt=\"\" width=\"205\" height=\"113\" \/><\/a> <a href=\"https:\/\/chartexpo.com\/TrafficTracker\/MTYrYmxvZytzZStjZXhwbytDRTY4OCs=\" target=\"_blank\" rel=\"noopener noreferrer nofollow\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2023\/04\/CTA-in-microsoft-excel.jpg\" alt=\"\" width=\"205\" height=\"113\" \/><\/a><\/div>\n<ul>\n<li>We&#8217;ll use the <a href=\"https:\/\/chartexpo.com\/blog\/sample-data-for-power-bi\" target=\"_blank\" rel=\"noopener noreferrer\">sample data<\/a> below for this example.<\/li>\n<\/ul>\n<table class=\"static\" style=\"table-layout: fixed; overflow-x: auto; border: 1px; font-size: 17px;\">\n<tbody>\n<tr>\n<td><strong>Total Cost<\/strong><\/td>\n<td><strong>Company Type<\/strong><\/td>\n<td><strong>Company Name<\/strong><\/td>\n<td><strong>Expertise Categories<\/strong><\/td>\n<td><strong>Expertise<\/strong><\/td>\n<td><strong>Cost<\/strong><\/td>\n<\/tr>\n<tr>\n<td>Total Cost<\/td>\n<td>Subcontractor<\/td>\n<td>Skyline Contractors<\/td>\n<td>Mechanical Installation<\/td>\n<td>Plumbing &amp; Heating<\/td>\n<td>15456<\/td>\n<\/tr>\n<tr>\n<td>Total Cost<\/td>\n<td>Subcontractor<\/td>\n<td>Skyline Contractors<\/td>\n<td>Mechanical Installation<\/td>\n<td>Mechanical Work<\/td>\n<td>10159<\/td>\n<\/tr>\n<tr>\n<td>Total Cost<\/td>\n<td>Subcontractor<\/td>\n<td>Onyx General Contractors<\/td>\n<td>Mechanical Installation<\/td>\n<td>Plumbing &amp; Heating<\/td>\n<td>18045<\/td>\n<\/tr>\n<tr>\n<td>Total Cost<\/td>\n<td>Subcontractor<\/td>\n<td>Onyx General Contractors<\/td>\n<td>Mechanical Installation<\/td>\n<td>Mechanical Work<\/td>\n<td>12695<\/td>\n<\/tr>\n<tr>\n<td>Total Cost<\/td>\n<td>Subcontractor<\/td>\n<td>Living Well Remodeling<\/td>\n<td>Mechanical Installation<\/td>\n<td>Plumbing &amp; Heating<\/td>\n<td>14589<\/td>\n<\/tr>\n<tr>\n<td>Total Cost<\/td>\n<td>Subcontractor<\/td>\n<td>Living Well Remodeling<\/td>\n<td>Mechanical Installation<\/td>\n<td>Welding<\/td>\n<td>11456<\/td>\n<\/tr>\n<tr>\n<td>Total Cost<\/td>\n<td>Supplier<\/td>\n<td>Power-up Builders<\/td>\n<td>Raw Material<\/td>\n<td>Cement<\/td>\n<td>20561<\/td>\n<\/tr>\n<tr>\n<td>Total Cost<\/td>\n<td>Supplier<\/td>\n<td>Power-up Builders<\/td>\n<td>Raw Material<\/td>\n<td>Steel<\/td>\n<td>32456<\/td>\n<\/tr>\n<tr>\n<td>Total Cost<\/td>\n<td>Supplier<\/td>\n<td>Five-star Construction<\/td>\n<td>Raw Material<\/td>\n<td>Bricks<\/td>\n<td>10253<\/td>\n<\/tr>\n<tr>\n<td>Total Cost<\/td>\n<td>Supplier<\/td>\n<td>Five-star Construction<\/td>\n<td>Raw Material<\/td>\n<td>Timber<\/td>\n<td>9000<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<ul>\n<li>Paste the data table above into the \u201cPower Query\u201d window. After that, select the \u201cCreate a dataset only\u201d option.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/select-create-a-dataset-only-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/select-create-a-dataset-only-after-learning-what-are-data-pipelines.jpg\" alt=\"Select Create a Dataset Only After Learning What are Data Pipelines\" width=\"650\" \/><\/a><\/div>\n<ul>\n<li>Navigate to the left-side menu, and click on the &#8220;Data Hub&#8221; option. Power BI will populate the data set list. If no data set has been created, you&#8217;ll get an error message.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/click-on-data-hub-option-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/click-on-data-hub-option-after-learning-what-are-data-pipelines.jpg\" alt=\"Click on Data Hub Option After Learning What are Data Pipelines\" width=\"650\" \/><\/a><\/div>\n<ul>\n<li>Choose the data set you want to use in the <a href=\"https:\/\/www.chartexpo.com\/charts\/sankey-diagram\" target=\"_blank\" rel=\"noopener\">Sankey diagram<\/a>. After that, you\u2019ll see Power BI populate the screen as shown below.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/choose-data-set-to-use-in-sankey-diagram-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/choose-data-set-to-use-in-sankey-diagram-after-learning-what-are-data-pipelines.jpg\" alt=\"Choose Data Set to Use in Sankey Diagram After Learning What are Data Pipelines\" width=\"650\" \/><\/a><\/div>\n<ul>\n<li>Click on the \u201cCreate a report\u201d dropdown. Next, select \u201cStart from scratch.\u201d<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/click-on-create-a-report-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/click-on-create-a-report-after-learning-what-are-data-pipelines.jpg\" alt=\"Click on Create a Report After Learning What are Data Pipelines\" width=\"650\" \/><\/a><\/div>\n<ul>\n<li>A Report Canvas, similar to the one below will appear on your screen.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/report-canvas-will-appear-on-screen-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/report-canvas-will-appear-on-screen-after-learning-what-are-data-pipelines.jpg\" alt=\"Report Canvas will Appear on Screen After Learning What are Data Pipelines\" width=\"650\" \/><\/a><\/div>\n<h3>Stage 3: Add the Power BI Sankey Diagram Extension by ChartExpo<\/h3>\n<ul>\n<li>To create the Sankey Diagram, you\u2019ll have to use an add-in or the Power BI visual from AppSource. Navigate to the right side of the Power BI dashboard, and open the Power BI Visualizations panel. Next, click the ellipsis symbol (\u2026) to import the Power BI Sankey Diagram extension by ChartExpo.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/click-3-dots-to-import-sankey-diagram-entension-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/click-3-dots-to-import-sankey-diagram-entension-after-learning-what-are-data-pipelines.jpg\" alt=\"Click 3 Dots to Import Sankey Diagram Entension After Learning What are Data Pipelines\" width=\"650\" \/><\/a><\/div>\n<ul>\n<li>When the menu opens, select the \u201cGet more visuals\u201d option.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/select-get-more-visuals-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/select-get-more-visuals-after-learning-what-are-data-pipelines.jpg\" alt=\"Select Get more visuals After Learning What are Data Pipelines\" width=\"650\" \/><\/a><\/div>\n<ul>\n<li>In the following window that opens, enter \u201cSankey Diagram for Power BI by ChartExpo\u201d in the highlighted search box. You\u2019ll see the \u201cSankey Diagram for Power BI by ChartExpo.\u201d<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/enter-sankey-diagram-in-search-box-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/enter-sankey-diagram-in-search-box-after-learning-what-are-data-pipelines.jpg\" alt=\"Enter Sankey Diagram in Search Box After Learning What are Data Pipelines\" width=\"650\" \/><\/a><\/div>\n<ul>\n<li>Click the highlighted \u201cAdd\u201d button.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/click-on-add-button-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/click-on-add-button-after-learning-what-are-data-pipelines.jpg\" alt=\"Click on Add Button After Learning What are Data Pipelines\" width=\"650\" \/><\/a><\/div>\n<ul>\n<li>Power BI will add the \u201cSankey Diagram for Power BI by ChartExpo\u201d icon in the visualization panel.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/power-bi-sankey-diagram-icon-in-visualization-panel-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/power-bi-sankey-diagram-icon-in-visualization-panel-after-learning-what-are-data-pipelines.jpg\" alt=\"Power BI Sankey Diagram Icon in Visualization Panel After Learning What are Data Pipelines\" width=\"239\" \/><\/a><\/div>\n<h3>Stage 4: Draw a Sankey Diagram with ChartExpo\u2019s Power BI extension<\/h3>\n<ul>\n<li>To do that, select the \u201cSankey Diagram for Power BI by ChartExpo\u201d icon in the visualization panel. After that, a window similar to the one below will open in the report section of your dashboard.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/open-in-report-section-of-dashboard-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/open-in-report-section-of-dashboard-after-learning-what-are-data-pipelines.jpg\" alt=\"Open in Report Section of Dashboard After Learning What are Data Pipelines\" width=\"375\" \/><\/a><\/div>\n<ul>\n<li>You have the option to resize the visual. Moving on, navigate to the right side of the Power BI dashboard, and look out for \u201cFields\u201d next to \u201cVisualizations.\u201d<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/lookout-for-fields-next-to-visualizations-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/lookout-for-fields-next-to-visualizations-after-learning-what-are-data-pipelines.jpg\" alt=\"Lookout for Fields Next to Visualizations After Learning What are Data Pipelines\" width=\"459\" \/><\/a><\/div>\n<ul>\n<li>Follow the sequence below when selecting the fields to use in the Sankey chart.\n<ul>\n<li>Total Cost<\/li>\n<li>Company Type<\/li>\n<li>Company Name<\/li>\n<li>Expertise Categories<\/li>\n<li>Expertise<\/li>\n<li>Cost<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/select-fields-to-use-sankey-chart-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/select-fields-to-use-sankey-chart-after-learning-what-are-data-pipelines.jpg\" alt=\"Select Fields to Use Sankey Chart After Learning What are Data Pipelines\" width=\"222\" \/><\/a><\/div>\n<ul>\n<li>You\u2019ll have to provide your email address or ChartExpo license key.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/provide-email-address-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/provide-email-address-after-learning-what-are-data-pipelines.jpg\" alt=\"Provide Email Address After Learning What are Data Pipelines\" width=\"650\" \/><\/a><\/div>\n<h3>Stage 5: Activate the ChartExpo Trial or Apply a Subscription Key<\/h3>\n<ul>\n<li>Select the ChartExpo visual. You\u2019ll see three icons below \u201cBuild Visual\u201d in the Visualizations panel.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/see-three-icons-below-build-visual-in-visualization-panel-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/see-three-icons-below-build-visual-in-visualization-panel-after-learning-what-are-data-pipelines.jpg\" alt=\"See Three Icons Below Build Visual in Visualization Panel After Learning What are Data Pipelines\" width=\"265\" \/><\/a><\/div>\n<ul>\n<li>Select the middle icon, &#8220;Format visual.&#8221; After that, the visual properties will be populated.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/select-middle-icon-format-visual-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/select-middle-icon-format-visual-after-learning-what-are-data-pipelines.jpg\" alt=\"Select Middle Icon Format Visual After Learning What are Data Pipelines\" width=\"246\" \/><\/a><\/div>\n<ul>\n<li>As a new user, you\u2019ll have to enter your email address in the textbox under the \u201cTrial Mode\u201d section. The license key will be sent to the email upon subscription. Toggle \u201cEnable Trial\u2019 to activate the 7-day trial.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/toggle-enable-trial-to-activate-7-day-trial-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/toggle-enable-trial-to-activate-7-day-trial-after-learning-what-are-data-pipelines.jpg\" alt=\"Toggle Enable Trial to Activate 7-Day Trial After Learning What are Data Pipelines\" width=\"233\" \/><\/a><\/div>\n<ul>\n<li>The Sankey Diagram you create under the 7-day trial comes with the ChartExpo watermark.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/sankey-diagram-with-watermark-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/sankey-diagram-with-watermark-after-learning-what-are-data-pipelines.jpg\" alt=\"Sankey Diagram with Watermark After Learning What are Data Pipelines\" width=\"650\" \/><\/a><\/div>\n<ul>\n<li>Enter the license key in the \u201cChartExpo License Key\u201d textbox in the \u201cLicense Settings\u201d section. After that, slide the toggle switch next to \u201cEnable License\u201d to \u201cOn.\u201d<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/enter-license-key-in-license-settings-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/enter-license-key-in-license-settings-after-learning-what-are-data-pipelines.jpg\" alt=\"Enter License Key in License Settings After Learning What are Data Pipelines\" width=\"235\" \/><\/a><\/div>\n<ul>\n<li>The Sankey diagram should be ready. It does not come with a watermark.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/sankey-diagram-without-watermark-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/sankey-diagram-without-watermark-after-learning-what-are-data-pipelines.jpg\" alt=\"Sankey Diagram without Watermark After Learning What are Data Pipelines\" width=\"650\" \/><\/a><\/div>\n<ul>\n<li>To add a Prefix (like the $ sign) with the numeric values in the chart, you\u2019ll have to expand the \u201cStats\u201d properties. After that, include the Prefix value.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/add-prefix-with-numeric-value-in-chart-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/add-prefix-with-numeric-value-in-chart-after-learning-what-are-data-pipelines.jpg\" alt=\"Add Prefix with Numeric Value in Chart After Learning What are Data Pipelines\" width=\"650\" \/><\/a><\/div>\n<ul>\n<li>To add colors to each node, expand the \u201cLevel Colors\u201d properties and select the colors.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/add-colors-to-each-node-after-learning-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/add-colors-to-each-node-after-learning-what-are-data-pipelines.jpg\" alt=\"Add Colors to Each Node After Learning What are Data Pipelines\" width=\"232\" \/><\/a><\/div>\n<ul>\n<li>The changes will be saved automatically.<\/li>\n<\/ul>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/final-what-are-data-pipelines.jpg\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2024\/11\/final-what-are-data-pipelines.jpg\" alt=\"Final What are Data Pipelines\" width=\"650\" \/><\/a><\/div>\n<div style=\"text-align: center;\"><a href=\"https:\/\/chartexpo.com\/utmAction\/MTYrYmxvZytwYitjZXhwbytQQkk2ODgrU2Fua2V5Kw==\" target=\"_blank\" rel=\"noopener noreferrer nofollow\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2023\/04\/CTA-in-power-bi.jpg\" alt=\"\" width=\"205\" height=\"113\" \/><\/a> <a href=\"https:\/\/chartexpo.com\/utmAction\/MTYrYmxvZytncytjZXhwbytDRTY4OCs=\" target=\"_blank\" rel=\"noopener noreferrer nofollow\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2023\/04\/CTA-in-google-sheets.jpg\" alt=\"\" width=\"205\" height=\"113\" \/><\/a> <a href=\"https:\/\/chartexpo.com\/TrafficTracker\/MTYrYmxvZytzZStjZXhwbytDRTY4OCs=\" target=\"_blank\" rel=\"noopener noreferrer nofollow\"><img decoding=\"async\" class=\"alignnone size-full wp-image-4345\" src=\"https:\/\/chartexpo.com\/blog\/wp-content\/uploads\/2023\/04\/CTA-in-microsoft-excel.jpg\" alt=\"\" width=\"205\" height=\"113\" \/><\/a><\/div>\n<h4>Insights<\/h4>\n<ul>\n<li>At Level 1 (Total Cost), the procurement cost is $155K.<\/li>\n<li>At Level 2 (Company Type), out of the $155K cost, $82.4K (53.3%) was spent on subcontractors, while $72.3K (46.7%) was allocated to the supplier.<\/li>\n<li>At Level 3 (Company Name), the supplier cost of $72.3K was divided between two companies: Five-star Construction and Power-up Builder, with charges of $19.3K and $53.0K, respectively.<\/li>\n<li>The subcontractor cost of $82.4K was distributed among three companies: Onyx General Contractors, Skyline Contractors, and Living Well Remodeling. They charged $30.7K, $25.6K, and $26.0K, respectively, for their services.<\/li>\n<\/ul>\n<h2 id=\"data-pipeline-vs-etl-pipeline\">What is the Difference Between Data pipeline vs. ETL pipeline?<\/h2>\n<p>A data pipeline is a broader term referring to the automated flow of data from one system to another, including processes like data collection, movement, and storage for various uses such as analytics, machine learning, or reporting.<\/p>\n<p>In contrast, an ETL (Extract, Transform, Load) pipeline is a specific type of data pipeline focused on extracting data from source systems, transforming it into a suitable format, and loading it into a target system like a data warehouse for analysis.<\/p>\n<p>Simply put, while all ETL pipelines are data pipelines, not all data pipelines are ETL pipelines, as managing data pipelines can also include real-time streaming, data replication, or data cleaning tasks without transformation steps.<\/p>\n<h2 id=\"advantages-of-data-pipeline\">What are the Advantages of Data Pipeline?<\/h2>\n<p data-start=\"101\" data-end=\"198\">Data pipelines offer several advantages that help businesses manage and utilize data effectively:<\/p>\n<ul>\n<li data-start=\"202\" data-end=\"340\"><strong data-start=\"202\" data-end=\"217\">Automation:<\/strong> Data pipelines automate the collection, movement, and processing of data, reducing manual tasks and saving time for teams.<\/li>\n<li data-start=\"344\" data-end=\"508\"><strong data-start=\"344\" data-end=\"373\">Consistency and Accuracy:<\/strong> By standardizing how data flows between systems, pipelines reduce errors and ensure your data remains clean and reliable for analysis.<\/li>\n<li data-start=\"512\" data-end=\"683\"><strong data-start=\"512\" data-end=\"535\">Real-Time Insights:<\/strong> Many data pipelines support real-time or near-real-time data processing, enabling businesses to <a href=\"https:\/\/chartexpo.com\/blog\/power-bi-kpi-dashboard\" target=\"_blank\" rel=\"noopener\">monitor key metrics<\/a> and respond quickly to changes.<\/li>\n<li data-start=\"687\" data-end=\"846\"><strong data-start=\"687\" data-end=\"703\">Scalability:<\/strong> As your data grows, pipelines can handle large volumes efficiently, ensuring your analytics and reporting processes remain fast and effective.<\/li>\n<li data-start=\"850\" data-end=\"1033\"><strong data-start=\"850\" data-end=\"879\">Improved Decision-Making:<\/strong> With automated, clean, and timely data delivery, teams can generate insights faster, supporting informed, data-driven decisions across your organization.<\/li>\n<\/ul>\n<h2 id=\"challenges-in-building-data-pipelines\">What are Challenges for Building Data Pipelines?<\/h2>\n<p data-start=\"101\" data-end=\"165\">Building data pipelines can bring several challenges, including:<\/p>\n<ul>\n<li data-start=\"169\" data-end=\"346\"><strong data-start=\"169\" data-end=\"193\">Data Quality Issues:<\/strong> Ensuring that incoming data is clean, accurate, and consistent can be difficult, especially when dealing with multiple sources and unstructured formats.<\/li>\n<li data-start=\"350\" data-end=\"513\"><strong data-start=\"350\" data-end=\"366\">Scalability:<\/strong> As data volumes grow, pipelines must handle larger loads efficiently without delays or failures, requiring careful design and resource management.<\/li>\n<li data-start=\"517\" data-end=\"696\"><strong data-start=\"517\" data-end=\"544\">Integration Complexity:<\/strong> Connecting various data sources, APIs, and destination systems often requires custom development and ongoing maintenance to keep pipelines functioning.<\/li>\n<li data-start=\"700\" data-end=\"885\"><strong data-start=\"700\" data-end=\"729\">Monitoring and Debugging:<\/strong> Identifying failures or bottlenecks in the pipeline can be challenging without robust monitoring tools, which are essential for ensuring smooth operations.<\/li>\n<li data-start=\"889\" data-end=\"1054\"><strong data-start=\"889\" data-end=\"917\">Security and Compliance:<\/strong> Safeguarding sensitive data while ensuring compliance with regulations (such as GDPR) adds complexity to pipeline design and management<\/li>\n<\/ul>\n<h2 id=\"tips-for-effective-data-processing-pipeline\">Tips for an Effective Data Processing Pipeline<\/h2>\n<ul>\n<li data-start=\"105\" data-end=\"243\"><strong data-start=\"105\" data-end=\"137\">Start with Clear Objectives:<\/strong> Define what data you need, why you need it, and how it will be used to guide pipeline design effectively.<\/li>\n<li data-start=\"247\" data-end=\"365\"><strong data-start=\"247\" data-end=\"277\">Ensure Data Quality Early:<\/strong> Add validation and cleansing steps during ingestion to avoid passing errors downstream.<\/li>\n<li data-start=\"369\" data-end=\"512\"><strong data-start=\"369\" data-end=\"397\">Automate Where Possible:<\/strong> Use automation for repetitive processes like <a href=\"https:\/\/chartexpo.com\/blog\/data-cleansing-techniques\" target=\"_blank\" rel=\"noopener\">data cleaning<\/a> and transformation to save time and reduce human error.<\/li>\n<li data-start=\"516\" data-end=\"654\"><strong data-start=\"516\" data-end=\"538\">Monitor and Alert:<\/strong> Set up monitoring and automated alerts to quickly detect failures, bottlenecks, or data anomalies in your pipeline.<\/li>\n<li data-start=\"658\" data-end=\"816\"><strong data-start=\"658\" data-end=\"685\">Design for Scalability:<\/strong> Build your pipeline to handle growing data volumes without performance drops, ensuring it remains reliable as your business grows.<\/li>\n<\/ul>\n<h2 id=\"top-5-use-cases-of-data-pipelines\">Top 5 Use Cases of Data Pipelines<\/h2>\n<ol>\n<li data-start=\"85\" data-end=\"211\"><strong data-start=\"85\" data-end=\"109\">Real-Time Analytics:<\/strong> Stream live data from sensors, apps, or websites to dashboards for instant insights and monitoring.<\/li>\n<li data-start=\"214\" data-end=\"317\"><strong data-start=\"214\" data-end=\"235\">Data Warehousing:<\/strong> Move and transform raw data into data warehouses for reporting and BI analysis.<\/li>\n<li data-start=\"320\" data-end=\"447\"><strong data-start=\"320\" data-end=\"351\">Machine Learning Pipelines:<\/strong> Automate data preparation, feature engineering, and model training workflows for ML projects.<\/li>\n<li data-start=\"450\" data-end=\"558\"><strong data-start=\"450\" data-end=\"469\">Data Migration:<\/strong> Transfer large volumes of data efficiently during system upgrades or cloud migrations.<\/li>\n<li data-start=\"561\" data-end=\"693\"><strong data-start=\"561\" data-end=\"579\">ETL Processes:<\/strong> Extract, transform, and load data from various sources into structured formats for consistent <a href=\"https:\/\/chartexpo.com\/blog\/business-analytics\" target=\"_blank\" rel=\"noopener\">business analytics<\/a>.<\/li>\n<\/ol>\n<h2 id=\"future-of-data-pipelines\">What is the future of Data Pipelines?<\/h2>\n<p>The future of managing data pipelines is moving toward automation, real-time processing, and AI integration. As businesses handle larger and more complex data streams, pipelines will increasingly use machine learning for <a href=\"https:\/\/chartexpo.com\/blog\/data-quality\" target=\"_blank\" rel=\"noopener\">data quality<\/a> checks and anomaly detection.<\/p>\n<p>Serverless and cloud-native architectures will make pipelines more scalable and cost-efficient, while low-code tools will enable non-technical teams to build and manage pipelines easily. Overall, data pipelines will become faster, smarter, and more accessible, empowering organizations to <a href=\"https:\/\/chartexpo.com\/blog\/data-driven-decision-making\" target=\"_blank\" rel=\"noopener\">make data-driven decisions<\/a> in real time.<\/p>\n<h2 id=\"data-pipelines-faqs\">Data Pipelines &#8211; FAQs<\/h2>\n<h3>What are Data Pipelines Used For?<\/h3>\n<p data-pm-slice=\"1 1 []\">Data pipelines are used to automate the movement and processing of data from multiple sources to destinations like data warehouses or analytics tools. They help clean, transform, and organize data, making it ready for reporting, analysis, and business decision-making efficiently.<\/p>\n<h3>What is a simple example of a data pipeline?<\/h3>\n<p>A basic pipeline involves the extraction of sales data from a CSV file, transforming it by calculating total revenue and loading the results into a database for analysis.<\/p>\n<h3>Is data pipeline the same as ETL?<\/h3>\n<p>No, a data pipeline is not the same as ETL. An ETL pipeline (Extract, Transform, Load) is a specific type of data pipeline focused on extracting data from sources, transforming it, and loading it into a target system.<\/p>\n<p>In contrast, a data pipeline is a broader concept that refers to any series of steps that move and process data from one system to another, which can include ETL, ELT, streaming data pipelines, and real-time data flows.<\/p>\n<h3>What are the main 3 stages in a data pipeline?<\/h3>\n<p data-start=\"638\" data-end=\"687\">The three main stages in a data pipeline are:<\/p>\n<ol>\n<li data-start=\"692\" data-end=\"793\"><strong data-start=\"692\" data-end=\"711\">Data Ingestion:<\/strong> Collecting data from various sources such as databases, APIs, and cloud services.<\/li>\n<li data-start=\"797\" data-end=\"899\"><strong data-start=\"797\" data-end=\"821\">Data Transformation:<\/strong> Cleaning, formatting, and processing the data to make it usable for analysis.<\/li>\n<li data-start=\"903\" data-end=\"1036\"><strong data-start=\"903\" data-end=\"920\">Data Storage:<\/strong> Storing the processed data in a data warehouse, data lake, or analytics platform for reporting and decision-making.<\/li>\n<\/ol>\n<h3>How to use pipelines in Power BI?<\/h3>\n<p data-start=\"1082\" data-end=\"1111\">To use pipelines in Power BI:<\/p>\n<ul>\n<li>Navigate to Deployment Pipelines in Power BI Service.<\/li>\n<li>Create a new pipeline and assign your workspace to the development stage.<\/li>\n<li>Deploy your Power BI reports and datasets from development to test, and then to production, using the structured stages for version control.<\/li>\n<li>Pipelines in Power BI help manage content lifecycle, ensure consistent updates, and simplify collaboration and governance while moving reports through development, testing, and production environments.<\/li>\n<\/ul>\n<h4 id=\"wrap-up\">Wrap Up<\/h4>\n<p>Data pipelines help organizations automate the systematic flow of data, and it also ensure timely, accurate, and organized movement. Data pipelines can be created in Power BI using Power Query.<\/p>\n<p>To get started, you have to import data from multiple sources, transform it using the Power Query Editor, apply necessary transformations, and load it into Power BI.<\/p>\n<p>One major benefit of using data pipelines is the scalability and flexibility that comes with it. A data pipeline is designed to scale, and it can handle increasing volumes of data without a hitch. The scalability of data pipelines makes it almost impossible for the data infrastructure to crumble under pressure, and that allows the business to expand seamlessly.<\/p>\n<p>By following the steps in this guide, you\u2019ll be able to easily use the ChartExpo visualization tool to create compelling visuals for your business.<\/p>\n","protected":false},"excerpt":{"rendered":"<p><p>Uncover what are data pipelines, why they matter, &#038; their role in simplifying data movement, ensuring integrity, &#038; supporting organizations with efficient analysis.<\/p>\n&nbsp;&nbsp;<a href=\"https:\/\/chartexpo.com\/blog\/what-are-data-pipelines\"><\/a><\/p>","protected":false},"author":1,"featured_media":44080,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[906],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\r\n<title>What are Data Pipelines and How They Support Insights? 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