Can you implement data masking when using IBM DataWorks Data Load API to protect confidential information?
Yes, IBM DataWorks Data Load supports data masking. The information on how to accomplish this can be found in DataWorks API documentation Integrating the Data Load REST API into your application. Here is an excerpt of that document:
... If you classify the data in a source column as sensitive, Data Load masks the data in that column when it is moved to the target
Note: This question was answered on dW Answers by user jcantella.
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I'm creating a pipeline in Google Data Fusion that allows me to export my bing-ads data into Bigquery using my bing-ads developer token. I couldn't find any data sources that should be added to my pipeline in data fusion. Is fetching data from API calls even supported on Google Data Fusion and if it is, how can it be done?
HTTP based sources for Cloud Data Fusion are currently in development and will be released by Q3. Could you elaborate on your use case a little more, so we can make sure that your requirements will be covered by those plugins? For example, are you looking to build a batch or real-time pipeline?
In the meantime, you have the following two, more immediate options/workarounds:
If you are ok with storing the data in a staging area in GCS before loading it into BigQuery, you can use the HTTPToHDFS plugin that is available in the Hub. Use a path that starts with gs:///path/to/file
Alternatively, we also welcome contributions, so you can also build the plugin using the Cloud Data Fusion APIs. We are happy to guide you, and can point you to documentation and samples.
We want to use google-cloud-speech to perform streaming speech-to-text conversion. If we enable data logging, will the audio data and the recognition metadata be saved in bucket associated with project?
No, and in fact, it's typically the other way around. You can upload your audio file to a Cloud Storage bucket, and the Speech API can read directly from that using a gs:// URL that you provide.
According to the documentation, Data logging just is for allowing Google to improve its models using the data you provide. It's not for remembering everything you ever did with the API.
I have a mobile app that uses Mobilefirst Cloudant sdk to work on top of Bluemix.
One type of the json document in the Cloudant DB needs to have an image as a field. Can you give me some example in Swift as how to store and read it?
I have a Cloudant local datastore on the device, it is synched with the server. So I shouldnot need to worry about the performance?
Thanks.
Jen
Assuming you are using CDTDatastore, you should use the attachment's API which is designed to hold binary blobs, such as images, see using attachments in the CDTDatastore documentation. You should also read up about attachments and their possible performance implications in the Cloudant Documentation
I am building a application where I am trying to use IBM Watson question & answer API.
Currently I see only corpus for Healthcare and Travel, but I would like to ingest Custom dataset suiting my needs. Can anyone please point me to right direction or exact API which does that or IBM already built explorer which I can use to upload the data files directly.
Thanks for the help
At this time you can not ingest corpus data into IBM Watson. That is coming in the future.
I would like to use a REST API as a data source for tableau. Is this possible in any way? The API service returns standard JSON, and I would think that would be an ideal scenario for tableau. Rather than connecting to some backend database behind the API.
Thanks
The web data connector does this and is in beta right now as noted by inox. See: https://www.tableau.com/web-data-connector
"The Web Data Connector will allow you to create a connection to almost any data that is accessible over HTTP. This can include internal web services, JSON data, REST APIs, and many other sources. It will not be supported in the initial launch of Tableau 9.0. Beta participants will be able to use a dedicated product key to continue building and testing connectors until the Web Data Connector officially launches."
Also, you can use the Extract API to create Tableau Extracts from an API: https://www.tableau.com/learn/tutorials/on-demand/extract-api-introduction