Astera ReportMiner vs. Paxata

ReportMiner is well suited for digitizing PDFs that includes data that follows a pattern such as a bank statement. It saves a bunch of time to make one report that will be able to be used each month for that bank. The program would not be useful if you had to spend the time making a new report each month for a new bank with a few lines of data

Paxata can be highly useful to someone who doesn't like/have any experience with writing codes to treat data before using it as input into BI dashboards. Paxata can accelerate data cleaning in environments where a large amount of unclean data is generated and business decisions on the go are required. It performs really well while dealing with natural language.

Incentivized

• It performs its function well, with flexibility and relative ease.
• Ability to easily convert PDF into text, especially in those situations where PDF documents have complicated formats.

• Visualize distributions in large data sets effectively which enable the user to quickly spot outliers and treat them appropriately
• Provides recommendation to merge datasets based on matching column values
• The cluster and edit feature in my opinion is its most powerful feature and reduces cardinality in column with text

Incentivized

• Could provide some features to help with advanced analytics for big data. (i.e. larger data sets)
• Too much clutter on their Youtube page, they should highlight the tutorials so they are easier to find for new users. Get rid of old tutorial video playlists so the organization is clean and up to date.
• Have sales rep follow up with customers to offer product updates, new product releases, and do check ins to see if customers have suggestions for feature improvement.

• Doesn't provide recommendation on how to impute values
• There is a lag quite often
• We can say whether a column has errors or quality issues in the first look

Incentivized

It is the best way to get a multi line record from pdf to Excel in one row.

Astera ReportMiner had a more concentrated feature stack for what we were looking for at a cheaper price so we went with it instead of other competitors that had more features, more complicated UIs, and had more expensive subscription packages because of it. They also had an easy purchase/setup process at the time of our procurement.

Paxata is a much better tool when it comes to handling natural language but Talend provides recommendations on how to impute missing values and outliers. Paxata provides recommendations on dataset tie-ups and joins but Talend doesn't provide any such recommendations. In paxata you can visualize distribution of data in a column and filter them by dragging and selecting the section you'd like to retain

Incentivized

• Efficient and automated data extraction. Saves time and resources.
• User-friendly interface and good documentation. It is therefore easiest to learn and apply in a short time.
• Documents, which have various formats of data tables or arrangement, needed a lot of manual fixing. So it required a lot of time for validation and quality control.

• It saves time to clean data
• It reduces the requirement of too many data engineer/stewards and hence adds positive impact on the return of the business

Incentivized