Usage for enterprise wide data management and governance across wide range of user group. Ataccama ONE enables achieving higher data quality amongst the data products. It is a powerful platform that supports integration of several checks on different data sets that can be also consolidated in reports later on. Data discovery works quite fast and easy.
Azure Data Lake Analytics services are beneficial when working with a lot of data. It can process enormous amounts of data extremely quickly. Service is secure and easy to set up, build, scale, and run on Azure. Regarding big data analytics and reporting, parallel processing has a significant impact. It consolidated our analytics from multiple systems and increased our analysis productivity. This tool has excellent support for reporting tools like Power BI and is very quick when performing analytics.
There's a bit of bias towards cloud with ADL Analytics. Depending upon a company's infra strategy and investment plans, there are some challenges with migration and integeration.
Not worth the time/effort/money if the organization doesn't have "Volume" of data. Cost effective only when daily loads exceed around 1million.
While training materials are available online, Adoption rate - Yet to pick up.
One of the key factors in our choice to onboard Ataccama was its usability - general end users have everything at their fingertips, it is not difficult for IT developers to setup the tool, and it has been an overall pleasure.
Ataccama ONE is a designated tool for Data quality monitoring. Supports end to end. Quite easy to deploy. Alteryx is more about coding or almost as complicated while Ataccama ONE is a bit easier to use. Different interfaces. Many views automatically available for data sets in Ataccama ONE. Output is vizualized in the tool. While more data transformation is required in Alteryx.
We did some research about Alibaba Cloud Data Lake Analytics and even being cheaper than Azure Data Lake Analytics, we decided to go for the second one once we noticed they have more features and better documentation. Another thing we considered during this process was the fact that we have more people that already have Azure Cloud knowledge.