What data should I share?
Rest assured that any information you provide will remain confidential, accessible only to those you authorize. Your data will not be utilized for AI model training and can be erased by you permanently whenever you choose.
Many individuals familiar with analytics tools may be inclined to share pre-prepared and summarized data when exploring inmydata for a proof of concept. While this approach will work, it doesn't showcase the full potential of our platform.
We understand the requirement to prepare and pre-summarize datasets to ensure performance is a major drawback for most analytics solutions. It enforces datasets tailored to very specific use cases, necessitating the creation of a new dataset for each dashboard or KPI. Consequently, this increases the workload for building and maintaining analytics content, places additional load on the business application to repeatedly process the same data for different KPIs, and reduces the flexibility of available views and drill-down options for users.
Inmydata addresses these challenges by offering a performant and flexible platform that can summarize millions of rows of data in a fraction of a second. It enables real-time transformation and augmentation of raw data to deliver the KPIs an organization needs. Business analysts can load transactional data into the data warehouse and build the necessary data structures for dashboards and KPIs directly in the cloud. This reduces the frequency of preparing and loading raw data from the business application and enhances the flexibility of available views and drill-down options for users.
It is also not required, or advantageous to pre-calculate values before loading data. For example, consider the average transaction value (ATV). If the data was summarized by store before loading, and ATV was pre-calculated, it would limit the ability to generate a report showing ATV by product. However, by loading transactional data and allowing the platform to calculate ATV, both charts become achievable.
Finally, the conversational analytics, automated insights, and forecasting capabilities of inmydata are much more effective when richer and more detailed data is shared.
Do I need to flatten my data before loading?
For the purposes of a POC, it's probably a good idea. inmydata does facilitate linked columns and blending of datasets in the platform. If you want to see these functions in action, by all means deliver several datasets and we can join them on the platform, however for most POC a single flattened dataset is the quickest way to quickly see the platforms performance with your data.
How do I share data for a POC?
The easiest way to quickly get started with a POC is to share flat files of data with us. These can be in pretty much any format, for example csv, Excel files, tab delimited text files, database table dumps. Simply share the files with us at https://inmydata.wetransfer.com and one of our team will get them loaded for you. If you require validation of the automated data connectivity to your data repositories as part of your POC, reach out to us, and our team of engineers will assist you in setting it up seamlessly.
