Last week, Trifacta introduced a free trial for Amazon Redshift. As we’ve seen a growing number of organizations leveraging AWS for their data management and analytics initiatives, we have put forth a ton of investment in ramping up our capabilities on the Amazon stack. In the fall, we announced a new serverless architecture on AWS, giving users the ability to dynamically scale computing up or down on the fly. Additionally, we released Wrangler Pro, a multi-tenant SaaS edition optimized for Amazon, leveraging S3, Redshift, EMR, and EC2, giving data teams the scale and AWS connectivity they need without any software or hardware to manage. Wrangler Pro is the ideal solution for small teams or departments and the perfect complement to Wrangler Enterprise, our customer managed solution for AWS. On the business side, we’ve seen 4x growth in the number of customers deploying Trifacta on AWS. A trend that is only accelerating.
For many data analysts, data scientists, and data engineers, the majority of their work is tied up in this data preparation and cleaning process. Traditional methods might use a combination of tools like SQL and code to blend data from databases and file systems. This process can be manual and cumbersome, requiring IT teams and siloed groups to build code, visualize and analyze the results, and debug when errors inevitably arrive. The explosion of cloud adoption led by AWS has only expanded the volume and variety of data organizations can utilize, but the data quality bottlenecks described above persist and are exacerbated by the speed at which cloud enables businesses to move. Organizations investing in cloud data lakes are landing large volumes of raw data that needs to be profiled, prepped, cleaned, and blended with disparate sources before being published to Amazon Redshift for analysis. Trifacta empowers data professionals of all levels of technical expertise to access, manage, and prepare data in Amazon Redshift and other AWS sources like Amazon S3.
Trifacta is being successfully used on AWS by a variety of different organizations – from some of the world’s largest financial firms, to emerging and innovative startups like Adaptive Analytics. Below are a few notable use cases:
- Consensus Corporation (a Target subsidiary) leverages Trifacta to decrease the time it takes to feed new data and update their fraud detection models for their retail customers. The company’s fraud detection models help save retailers from selling merchandise to illegitimate customers, saving them massive amounts of otherwise lost revenue every year.
- Deutsche Borse leverages Trifacta on AWS to drastically decrease the time it takes for their data science team to work with new data sources. Deutsche Borse’s data science team is then able to focus on driving improvements to their data marketplace for their customers
- Tipping Point Community leverages Trifacta to prepare a variety of publicly available datasets, which ultimately helps them analyze how to break the cycle of poverty for individuals and families in the San Francisco Bay Area. With Trifacta, the Tipping Point Community can quickly join together these data sets and import them directly into Tableau, greatly reducing their time spent on data preparation since switching from Excel.
Trifacta integrates natively into existing AWS services to provide a seamless experience within the AWS ecosystem. We leverage IAM roles to authenticate and respect permissions to data set up within AWS. Trifacta can read data from and write to S3 and Redshift and transformations scale to large volumes of data by leveraging Spark to execute on fully managed EMR clusters, getting all of the benefits of scale that EMR provides with none of the management overhead.
Trifacta’s free trial of Wrangler Pro for Amazon Redshift supports teams of up to 10 users and comes with a compute limit rather than a time limit. Try it out and let us know what you think.