Building AWS Big Data Pipeline - Overview, Uses, and Benefits

• With data growing at an exponential pace, organizations are facing difficulties in data management. From processing data to storing it or migrating to other systems, everything has been a bit complicated and time-consuming. This, in turn, reduces employees’ work efficiency and efforts.

• There are many issues that organizations face with data management. A few of them are listed below –

• A Large Amount of Raw Data – There is a lot of unprocessed data like – log files, demographic data, sensors data, transaction histories, and much more.
• Varied Formats of Data – With data available in multiple formats - .doc, .jpg, and many more. Converting it to a compatible format is a time-consuming and complicated task.
• Different Data Storage – Companies can store data anywhere they want. Be it warehouses, cloud-based platforms, or various databases. This sometimes creates problems in deciding which could be the right way to store data and access it whenever they want.
• Money & Time Consuming – Managing and maintaining a large amount of data costs companies a lot of money, time, and team efforts.

These challenges make it complex for companies to deal with large data. This is where AWS Big Data Pipeline has a major role to play. It can easily integrate data to AWS cloud services and enable quick access for the same at a centralized location. Let’s learn more about the AWS Data Pipeline below.

An Overview of AWS Big Data Pipeline

AWS Data Pipeline is a web service that streamlines data processing and transferring it between multiple AWS cloud computing services.

With AWS Big Data Pipeline, organizations can enable easy access to data to their employees. They can access it from any place or device and process it to any Amazon cloud services like –

• Amazon S3
• Amazon RDS
• Amazon DynamoDB
• Amazon EMR.

Through simplified creation of complex batch processing workloads, you can ensure a system that is the most relevant, scalable, and flexible.

What Are the Batch Data Pipeline Solutions?

Batch Data Pipeline Solutions is the best way to process a large number of datasets. This includes collection data, transforming it, and sinking resulting data to the destination.

With most organizations have transactional data, they need an efficient Batch Data Pipeline that can move data to the warehouse.

Here are 3 Batch Data Pipeline Solutions or Tools that can streamline the entire process:

• AWS Glue – Glue jobs are written with the help of RedShift Spectrums that can query the data stored in S3.
• Pentaho – This is an open-source tool that ensures seamless batch processing of data.
• AWS DMS – This tool is used to populate data in real-time to Redshift.

Uses of Amazon Data Pipelines

There are 6 major uses of these data pipelines that you can explore for your organization’s growth.

• Copy RDS or DynamoDB tables to S3.
• Run analytics using SQL queries and load it to RedShift.
• Analyze unstructured data and mix it with structured data from RDS and later transfer it to Redshift for querying purposes.
• Copy knowledge from the user on-premises knowledge store.
• Sort of MySQL information and move it to an AWS data store.
• Periodically backup the user dynamo dB table to S3 for disaster recovery functions.

Why Choose AWS Data Pipeline? 5 Major Benefits to Consider!

Let’s discuss the key benefits of using AWS Big Data Pipelines for your streamlining organization’s major operations.

• 1. Reliable

  AWS Data Pipeline is built upon highly accessible and distributed infrastructure to ensure flawless execution of your organizational activities.

  If you face any failure in data processing, Amazon data Pipelines can mechanically redo the activity. If the failure continues to persist, the Data Pipeline will alert you with the failure notifications via Amazon Simple Notification Service.

• 2. Flexible

  AWS Data Pipeline benefits you with a wide range of options for planning, dependency pursuit, and error handling. By using the AWS Big Data Pipeline features, you can write your custom activities or conditions.

  This shows that you can easily assemble an Amazon data Pipeline to do the following things

  • Run Amazon EMR jobs
  • Execute SQL queries against databases
  • And execute custom applications running on Amazon EC2 or in your datacenter.

  This forms a powerful system to analyze and process big data without expecting any complexities during execution.

• 3. Scalable

  Amazon Web Server Data Pipeline makes it quite simple for organizations to dispatch the data to multiple machines in serial or parallel. It can process more than 10 lakh files at the same time with sheer ease and convenience.

• 4. Easy to Use

  Creating pipelines with Amazon Cloud Computing Services is a fast and simple method.

  It eliminates the need of writing any additional logic to process the data. Accessing the Amazon S3 file or checking for its existence is quite easy. You need to provide the name of the Amazon S3 bucket and the path of the file. Rest information will automatically appear on the screen.

  It also provides a library of pipeline templates to form pipelines for the variety of additional advanced use cases.

• 5. Transparent

  Get full control over the procedure resources that help you execute the business logic and create them in simplified ways. It offers persistent and elaborated insights into what is going on in your pipeline.

  Apart from all the above benefits, AWS Data Pipeline is highly affordable and easy to use. It is billed at a very low cost. Isn’t it a great way to streamline data processing and managing?

Conclusion –

From the benefits mentioned above, you know how AWS Data Pipeline is useful for your organization. It is cost-effective and charges only based on the number of preconditions and activities used by the company each month.

By connecting to the cloud or on-premise data sources, you can have the flexibility to migrate the data to any platform you want. If you are looking forward to implementing these data pipelines to your system, avail of our AWS Cloud consulting services.

Being a certified AWS partner over the years, we know what works best for your organization. Bring transformation to the way you manage and process big data.