Adding your dataset
Note
You can also add a dataset to your project or manage your dataset using the SDK.
You've created a project and you've uploaded your properly formatted data to Amazon S3. Now it's time to add the data to the project.
Setting your permissions
Lookout for Equipment requires permissions to access your data in Amazon S3, and to publish information about ingestion validation to CloudWatch Logs.
On the Ingest dataset page, under Data source details, under IAM role, select your preferred method of giving Lookout for Equipment the appropriate permissions.
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Create an IAM role is the default. If you select this option. Lookout for Equipment will create a role for you with the appropriate permissions.
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Use an existing role. If you have previously created an IAM role that you want to use with this dataset, you can select it here.
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Enter a custom IAM role ARN. This is another way to choose an existing role.
Logging your ingestion data
If you are creating a new role, you can check the box indicating that you want Lookout for Equipment to store log data in Amazon CloudWatch Logs.
You can also enable logging by modifying an existing role.
When you enable logging, Lookout for Equipment will record information about errors in the files submitted for ingestion. For example, the logs may help you identify duplicate timestamps, missing or invalid data, or rejected files.
For more information, see Viewing your ingestion history.
Choosing your schema
You have multiple options in how to structure your data in Amazon S3. Your choice of those options should be guided by one of two approaches.
Approach A: Your data is already organized in a particular way, and you prefer to keep it that way. In this case, choose the option below that best matches the way your data is currently organized.
Approach B: You haven’t yet organized your data. In that case, examine the options below, and choose one that looks easier to implement. Then organize your data according to that option.
Before you proceed, be sure your data is formatted correctly.
Note
The following options assume that your files and folders have been organized by asset, which is what we recommend.
However, organizing them by sensor, according to the same pattern, is also possible.
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Option 1 (by filename):
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The name of the asset is the complete name of the CSV file.
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All sensors from that asset are represented in that one CSV file.
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The rest of the hierarchy of your Amazon S3 bucket doesn’t affect the ingestion of data for this asset.
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You can place multiple asset files into one folder.
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There is one CSV file per asset.
This is a good option if you have a small set of files, each named after a specific asset.
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Option 2 (by part of filename):
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The name of the asset is part of the name of the CSV file. (Specifically, it's the part of the filename that precedes the delimiter.)
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The rest of the hierarchy of your Amazon S3 bucket doesn’t affect the ingestion of data for this asset.
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There are multiple CSV files per asset.
This is a good option if you have to break up large files and give the smaller files similar names, such as pump1_january.csv and pump1_february.csv.
If you choose this option, then you must choose a delimiter. The delimiter indicates which character you are using, within the filename, to separate the name of the asset from the name of the sensor.
If applicable, select your delimiter from the dropdown menu at the bottom of the console window.
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Option 3 (by folder name):
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The name of the asset is the complete name of the folder containing one or more CSV files.
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The hierarchy in Amazon S3 is as follows:
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Inside the Amazon S3 bucket is the folder you select when you specify the Amazon S3 location of your data source. Within that folder is a folder named after the asset.
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Inside that folder are all the CSV files for that asset.
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There can be multiple CSV files per asset.
This is a good option if you have many files with long or inconsistent names, or a custom folder heirarchy that you want to retain.
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Uploading your data to Amazon S3
You have organized the .csv files that contain your data. Now, the next step is to upload those files to Amazon S3.
Moving your data to Amazon S3 is a prerequisite to ingesting your data.
Choose Create bucket
Under Bucket name, enter the name of your bucket. It might be useful to give your bucket the same name as your project, but that's optional.
Choose Create bucket
On the page with the list of buckets, choose your new bucket.
Choose Create folder.
Name your folder.
If you chose to use one file for each asset, then the folder should be named after the facility.
If you chose to use one file for each sensor, then the folder should be named after the asset.
Choose Create folder.
Choose the folder you created.
Choose one of the Upload buttons.
On the Upload page, choose Add files.
Add the appropriate files from your computer.
Choose Upload.
Return to the Lookout for Equipment console.
On the Ingest dataset page, under Data source details, indicate the location of the files you uploaded to Amazon S3.
So far, you've created your project, and (on this page) you've uploaded your well-organized data. Now it's time to integrate those steps by adding your uploaded data to your project.
Instructing Lookout for Equipment to ingest your data
You've set your permissions, chosen your schema, and (if applicable) chosen your delimiter. Now it is time for Lookout for Equipment to ingest your data.
Return to the Ingest dataset page.
Choose Ingest dataset.
You've ingested your data, but it's possible that there was an issue with the files, the sensors, or the ingestion job as a whole. To find out, you must now review data ingestion.
