Building a Heroku ETL pipeline can seem like a daunting task. The process seems complicated, and it's hard to know where to start. This post will show how easy it is to build an ETL pipeline with Heroku and Hadoop — and how Xplenty can help simplify the process.

Table of Contents

  1. Intro to Heroku
  2. What is ETL?
  3. What is an ETL Pipeline?
  4. ETL Benefits for Your Business
  5. Selecting Your Heroku ETL Database
  6. Intro to Hadoop
  7. Benefits of Hadoop
  8. Setting Up ETL in Hadoop
  9. Simplifying Hadoop and Heroku ETL with Xplenty

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Intro to Heroku

Heroku is a cloud service platform that anyone can use. It has been growing in popularity lately because its focus on user-friendliness makes the development and deployment of apps easier to implement than ever before.

Heroku lets companies build, deliver, monitor, and scale apps automatically. This gives you more time to explore user experience possibilities instead of working out infrastructure problems, such as how many server farms you need.

What is ETL?

The ETL process is one of the most popular forms of data integration today. Extracting, transforming, and loading are the three stages to this process:

The process first extracts information from various sources like databases, websites, or applications.

Next, the process transforms the data — correcting it by removing outdated or duplicate pieces and adding them all together into a centralized database with a uniform structure for easy analysis.

Finally, the complete set of collected data loads to an analytics system so you can quickly analyze what's going on across your business in real-time.

What is an ETL Pipeline?

An ETL pipeline is a specific process that extracts and transforms your data before it loads to the destination.

For data governance, automated ETL pipelines help companies ensure their BI and analytics workloads always have up-to-date information. In addition, by performing this work regularly, businesses can make sure they never miss out on an opportunity because of outdated or inaccurate information in the enterprise's data warehouse.

ETL Benefits for Your Business

Customer Data in Real-Time

Today, more than ever before, companies struggle to compete with other companies for customers. A business can effectively cut through the noise by leveraging its customer data and providing an engaging experience. Customer interaction information offers insights into what the most profitable demographic wants in terms of products or services. This can help you close deals faster and retain existing clients.

Easy Onboarding of Partners

IT teams create complex data pipelines to ensure seamless information exchange. With businesses onboarding new partners and associates every year, IT needs to code custom workflows for each of these companies — a tedious task that can take up valuable time they could spend elsewhere on the company's system.

Now, onboarding doesn't need to be such a hassle. With self-operating and self-regulatory processes, you'll get insights that will make your partnerships more beneficial and cost-efficient. Furthermore, the onboarding process can complete in hours instead of weeks.

ETL Tool

The ETL tool is the perfect solution for those looking to process data and integrate it with their analysis or production use cases. Not only does this software save you time, but it also helps you maintain peace of mind and improve efficiency within your company.

Some ETL tools require low coding, so people who don't have technical backgrounds can manipulate data. With this type of tool, people in all departments can access the data they need without having a developer on-site for every project.

Versatile Infrastructure

A good ETL tool solution will allow you to quickly and easily apply versatile data transformations without coding. In addition, you'll be able to integrate data from multiple sources into a single, streamlined process with ease, thanks, in part, because you can aggregate, filter, and sort as needed.

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Selecting Your Heroku ETL Database

You need to choose your database carefully. Some databases are better for analytics, while others provide reliability at scale. The Heroku database is a vital part of the data pipeline.

The Heroku Postgres database is the most used option among enterprise clients. It is an open-source SQL running on a relational database management system. If you're looking for a Heroku ETL solution to help with data integration, Xplenty is the way to go. With sophisticated pre-built integrations and features that allow many types of data transfers, this tool makes life easier.

Intro to Hadoop

Hadoop is a software framework that stores and analyzes large amounts of data. It provides massive storage and enormous processing power, and it can take concurrent tasks or jobs through parallel processing. As a result, Hadoop is the bedrock behind big data technologies that support advanced analytics initiatives such as predictive analytics.

Xplenty users should also consider Hadoop to better manage data. While Xplenty can already identify and sort information, Hadoop can improve upon the process.

Benefits of Hadoop

Hadoop is a powerful tool that provides many benefits. Some of the most critical are:

  • Preventing data corruption and identifying risks before they happen.
  • Improving performance to ensure hardware failure can't occur.
  • Helping to identify warning signs common for security breaches so your business stays safe from intrusions into private information like financial records or account passwords.

With these features and others, Hadoop has helped countless businesses maintain reliable access to their sensitive data while safeguarding against damaging leaks.

Setting Up ETL in Hadoop

Setting up a Hadoop Cluster

You can create Hadoop clusters with a few clicks on the Cloud or locally, depending on your needs. Cloud-based Hadoop services offer data analytics with low upfront costs and minimal management. However, while an internal cluster requires more planning, it provides greater control over performance, as well as ease of access to archived data.

Connecting Data Sources

Data architectures also require careful planning, as they must handle a range of input types and rates. Start small with your data architecture project so you can incrementally expand the scope at each stage and until it meets all of your analytic requirements. Then, combine this data infrastructure structure with business intelligence tools for even more robust insights.

Create Metadata

One important aspect of Hadoop is that you can store data and then decide what to do with it later. But before deciding to put your information in a system like this with no context or structure, it is important to define metadata for analytics purposes. Having documented metadata standards throughout your organization will allow users not only greater clarity about their data sets, but it will also remove ambiguity from the fields they view and manipulate on screens.

Make ETL Jobs

Transform data from various sources into a precise analysis or report. From technologies such as MapReduce and Cascading to Pig and Hive for designing ETL jobs, you'll have the framework you need to make sure your work is efficient.

If you need to extract data from a file or database, consider the type of job. A batch-only approach may not work well for your needs if new sources are coming in as streaming jobs do. This is because it takes all files and processes them before saving the results in one large file — which might already be outdated when the process finishes. Streaming creates separate queries with individual updates. As a result, you can quickly access recent information without lengthy waits between batches.

Structure a Workflow

When constructing workflows, it is essential to consider dependencies. The workflow itself can capture these dependencies and ensure that data transformations execute efficiently. Frequent ETL processes need not have any bottlenecks or slowdowns because they're performed parallelly. The execution schedule of these tasks is also an important consideration when designing your flowchart.

Simplifying Hadoop and Heroku ETL with Xplenty

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The Xplenty platform blends perfectly with Heroku and Hadoop.

Xplenty is a cutting-edge data platform that has the ability to make raw, unprocessed business intelligence more usable and user-friendly by filtering through this information with an intuitive point-and-click interface.

Xplenty has a drag-and-drop interface that lets you design complex data integrations in minutes. This process used to take hours for IT teams, but with Xplenty it can be done quickly and easily by anyone, even those without knowledge of coding.

In this new age of business, companies can get overwhelmed with their data like never before. You need to make sure you have information from all of your apps and visibility of your data, so your company thrives. If not, that could spell disaster for both your employees and customers. Connecting them with a common thread is one way to do it- no part will be left behind or forgotten about.

Xplenty allows you to connect your data sources without involving the IT department. With 140 pre-built connectors, Xplenty offers a variety of connections for any situation and eliminates technical roadblocks so even novices can use them with ease.

Ready to learn how it will work with cloud-powered databases? Sign up for a 14-day demo today and see firsthand what you can achieve in two weeks.