Why you should move your Big Data processing to FME

As your organisation consumes more and more data from complex sources such as sensors, data streams and IoT; the challenges facing your data teams are accelerating quickly. With so much information out there to digest, it begs the question: How is your team supposed to get insight out of Big Data as quickly as it comes in?

Well, they may already hold a licence to the perfect tool for the job. FME.

 

The problem with traditional ETL Tools

There are two core problems that most Data Teams face when trying to utilise Big Data:

  • Their current ETL tools aren’t up to the job.

    Traditional ETL tools batch process data as it come in, storing the data in internal memory as jobs take place. With higher volumes of data, this can cause the software to struggle and crash before processing has concluded.

  • Specialist tools carry a high cost.

    Software built specifically to handle Big Data can carry an equally big price tag. Once purchased, there is also the additional cost of training team members to use the software effectively and maintaining those skills as teams grown and change.

This leaves organisations that want to work with Big Data with no choice but to use a specialist Big Data ETL tool to manage the size of the data they’re working with, before chunking into more specialist software such as FME to perform the analysis needed to derive the real value.

 

 

Leveraging your existing investment to tackle the challenge

Safe Software, the makers of FME, recognised the challenge that working with these datasets bring and, in response, have heavily invested in developing FME to ensure that it can now credibly deal with Big Data.

 

Big Data integrations

For Big Data specifically, there are now 21 integrations including Hadoop Distributed File System, Google BigQuery and Microsoft Azure.

One of the most interesting integrations bought in for v2021 is the Apache Parquet reader/writer. Apache Parquet is column-based storage format that’s perfect for large, complex datasets. It allows data to be pulled into FME in more manageable chunks, making processing more stable.

 

Improved Parallel Processing

Parallel processing enables users to distribute the load of larger jobs across multiple cores/engines at the same time. By spreading the heavy lifting, processing time can be dramatically reduced.

Parallel processing first came to FME way back in 2012 but creating workspaces that effectively used this feature was complicated. With that in mind, Safe Software redesigned parallel processing in to make it easier for users to design workflows that use it to improve performance.

 

Utilise the software you already work with

The improvements and integrations that Safe Software has bought to the FME platform mean that your team can now be use it as an end-to-end solution for working with Big Data. At the front end, FME can securely ingest high volumes of raw data. During processing, jobs can be split down into manageable lots and processed in tandem to speed up results. These completed outputs can then be used to generate real value for your organisation.

Keeping your data within a single software environment ensures that your team can quickly and efficiently perform the steps needed to extract this value. We’ve experienced these improvements first hand, with our consultants using FME to support both internal and external projects that utilise large volumes of complex data.

Leveraging your investment in FME also helps to reduce operational costs by removing the need for additional software licences and training. Combining the benefits of a Big Data ETL tool and a Data Integration Platform, your team has everything they need in one place.

 

 

If you want to scale up your Big Data processes, download your version of FME 2021.1 today.

Need a little help? We’re always here to answer your questions! All you need to do is get in touch.