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Jobs to be Done Hierarchy for Enterprisey stuff
Apply (use) data to…
Jobs to be Done Hierarchy for Enterprisey stuff
Apply (use) data to drive my business / policymaking / (society)
When I want to use/apply data to our needs we need to find data and be able to use/prepare it (for both humans and machines) … and build flows to do that ...
[Manage] When looking at all the data in my org I want to organize / manage / make available data (in my organization) so that it is easy to discover and use, esp now that there are so many sources and use cases
I want to be able to "data enable" my organization by making "data exchange" easy and quick to do ... so that people can make use of data as needed (including for ad-hoc and unplanned uses), on demand and across teams and silos
👐 [Share (& store) data] When sharing data within our company (either ordinary users or more data techy people) I want to be able to do that quickly and easily for small or large files (and start to have a registry so we don’t depend on the data social network) so that people can get the data they need quickly
When sharing data, I want to know how often and when it is used, so that I can [scale system, update publishing, source new data that people are using]
When sharing data, I want consumers to be able to consume data in various formats (api, raw access, etc) so that can leverage data with existing tools.
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🖨️ [Publish/Present] When sharing (publishing?) data I’ve created (in my company / gov department), I want an easy way to store, control access, and provide metadata for my data, so that it can be discovered and used by others.
When publishing data, I want to be able to control access to the data, so that it can be discovered and used selectively based on business needs.
When publishing data, I want to be able to store lineage information with the data, so that the source and authenticity can be validated.
When publishing data, I want to be able to record metadata for the data, so that I can provide contextual information to consumers.
[something about data quality enhancement, metadata enhancement, standardisation, etc.]
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🛠️ [Consume/Use] When managing data in a platform, I want to be able to easily move data in and out, and integrate with existing systems, so that data is easily consumable by humans and machines
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[i want to easily integration with existing systems, so that teams ca use tools that currently rely on ...]
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🔭 [Discovery] [I want to find the data i want quickly so that i can do my project] When searching for data I want one (or very few) places to search so that I can find what I want quickly (or know it probably does not exist)
When building a data management system, I want it to be easy for publishers to get data in, edit it, and remove it, so that the goal of central discovery can be realised.
When building a data management system, I want to integrate data from across diverse sources so that I don't need a separate tool for this
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🔬 [Analyze] I want to analyze my data / build data driven apps => data science, BI etc
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🤖 [Integration / Automation] I want to automate manual data integration (processing) or improve quality, scale, complexity of automated data integration so that i can use that data to drive my business
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I want the flexibility and freedom to evolve my system for future needs so that I can future proof and avoid stranding investments and integrate the diverse systems and tools i haveWhy?? See this diagram about explosion in use cases and tech (plus data os post)
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