Getting started with aivis is easy. All you need is your data and a few basic data formatting skills.
Am I ready for aivis?
You are ready for aivis, if you have any datasets, time-series or tabular, that are available for export and csv conversion. And if you have a question or data analytics requirement connected to that data like why is something happening, what is happening and more.
Since the data might contain critical content or personal information, you also have to make sure, that you have the rights and are allowed to use this data with data analytics services like aivis.
Am I qualified to use aivis?
You are qualified to use aivis by yourself, if you have a general understanding of your dataset and are able to convert it into the target format for aivis.
In particular, you do not need any data science expertise, since all required expertise is already built into aivis. All the questions you need to answer to start an aivis calculation, can be answered if you have a general understanding of your processes and data. The same goes for interpreting the results.
If you are not sure, just contact our experts!
How do I make use of my data?
You have two basic options, how to make use of your data:
Analyse historical data: You do this to find relationships, dependencies, root causes, influencing factors and reactions within your data that might be prone to error or just unknown so far. This might enable immediate efficiency improvements. You also use historical data to learn from past behavior and build and train models for, e.g., virtual sensors or predictions in general.
Work on live data: A trained model is a piece of software that you can integrate or deploy on-edge, on-cloud or on-site to consume live data streams. It can e.g. predict specific behavior and particular quantities or warn in time about emerging problems. Use it to ensure quality, increase safety, raise throughput, and much more.
What kind of data do I need?
There are two basic types of datasets you can use aivis on: Time-series data and tabular data.
Time-series data consists of data points, that usually come from a sensor or signal and are associated with a timestamp that determines when exactly the value was set or received. Read more about time-series data on wikipedia. See also the aivis time-series data specifications.
Tabular data entries are usually created when an event or state is logged. Although it might contain timestamps, it can also be completely time-independent. Compared to time-series data, where a value is taken e.g. every second, tabular data is more event or state oriented. It might also describe not a point in time, but time frames. See also the aivis tabular data specifications.
The amount of data can be anything between a few kilo bytes (kb) and many terra bytes (tb).
How to prepare my data?
Whether you have time-series or tabular data, aivis works best with raw data as little processed as possible. Especially no records should be removed or interpolated. Time-series data does not have to be synchronized, nor is it necessary that the timestamps are equally distributed.
Data transfer: You can either upload the data with the aivis Insights app or store it in your own Amazon AWS S3 storage and create a user with privileges to read the dataset. For larger data volumes, it is possible to send hard drives with the data to us.
Will my data stay under my control?
Yes. Every dataset we receive is strictly confidential, not saved permanently, not duplicated, remains fully under your control and will be used for your own purposes only. An NDA can be set into place.
Get started with aivis Insights
aivis Insights is your perfect starting point. Quick and simple, it creates a report based on your data regarding your WHY. It is also the first step to check out if you have enough data for aivis Predict or Prevent.
Not sure what you need yet? No problem. Just relax and have a look at our products.