May 3rd, 2022 | Presenters: Brian Corcoran and Dan Valente | Recording | PPT slides (internal only)
Key Takeaways:
- Data access is fundamental. It's the starting point for any analytic journey. That's why, with JMP, we make it easy to access your data from a variety of sources.
- This is a strong focus of product development in the next few releases. We need your help in understanding the need and identifying requests around data connectors/data access.
- NEW EXTERNAL RESOURCE: Data Connectors Page that lists all of the different ways to connect to data (linked from the workflow page, data access section)
Broadly, and not perfectly, JMP gets data from three sources:
- Flat files (Files, Docs, 3rd Party Files)
- Databases (Databases)
- Web server-based programming interfaces (Webpages, Web API's, Cloud Sources)
"Does JMP support this?" Decision Tree
Discovery Questions:
- Where is your data stored?
- Who has access to it?
- Do you need to combine it from disparate sources prior to analysis?
- Do you have a corporate initiatives/digital transformation efforts in progress that we should be aware of?
What is a database?
- A repository for structured data, generally collected from other sources
- Often supports powerful query capabilities
- Structured means regular, with well defined variables (think JMP columns)
- Often provides a standardized way to access the data to third party applications like JMP
Why do organizations use databases?
- Databases provide an efficient way to store and quickly access large amounts of data.
- Databases provide powerful backup and restoration mechanisms to make sure data is not lost.
- The structure of databases makes complex queries possible.
- SQL is the most commonly used query language.
- Databases can be accessed by many other applications and tools within an organization.
Where do databases reside?
- Generally, a very capable server. This could be Linux, Windows or Mac
- The server can be on-premise and behind an organization’s firewall
- The server could also be with a Cloud provider like Amazon or Microsoft Azure. These providers mask the intricacies and make accessing and populating the database relatively easy
- In some cases, like Amazon Aurora, the database is distributed across many servers that provide redundancy and quick failover
How does JMP connect to a database?
- Query Builder is the preferred tool.
- Does JMP know how to connect directly to a database? No. You will need an ODBC driver to acts as a broker. The driver knows the peculiarities to be able to get the data back into a defined form.
Q: Hey, we just put our data in ___. Do you have a data connector for…
- Is there an ODBC driver? – Yes!
- If there isn’t an ODBC driver, is there an API? – Yes! Using HTTP Request.
- If you don’t want to work with the API, can you export a file or Excel file? – Yes!
Q: I don’t want a driver or to use the API. I just want File > Open.
- We are working towards adding direct data connects with the vision of File -> Open.
- Google Sheets (As easy as File -> Open)
- Query Builder (Abstracting out the complexity of SQL from S+Es that don’t have those skills)
- OSI Pi in JMP 17 (Direct access to a data historian…)
- Beyond JMP 17. A more unified broad strategy around data connectors (enable users to build their own library of data connectors).
Actual Data Connectors/Data Access questions pulled from the community:
- Can you access data stored in Snowflake?
- We’ve got data in LIMS. I don’t see a way to connect to that in the file menu.
- I want to access data in cloud sources that don’t have ODBC drivers.
- I want to connect to AWS S3.
- I need to connect to data on a network drive.
- Why can’t I access to my Microsoft Access database?
- What’s the best way to get data from MongoDB or Hadoop?
- Can I access data through pig with HTTP Request? We’ve got a Hadoop cluster running in pig or spark.
- Can you get data from Google BigQuery?
- It’s hard to get Office365 cloud data.
- I want to connect to spark tables using the DataBricks ODBC driver. Can I do this?
- I have performance issues with the Cloudera Hive ODBC driver.
Who should care about data connectors?
- IT/Data Managers
- Reduce the number of “can you build me this data set?” and one-off queries.
- Democratize the easy queries; more time for the challenging ones.
- Engineering Managers
- Making decisions from up-to-date data.
- Reduce the “well this is the data I set I had on my computer…”
- Decision Makers
- Business critical decisions made on up-to-date data.
- Cost, time and efficiency gains.
Competitor Data Connector Information:
What if a customer requests a data connector that is not supported. How can I provide that feedback?
One of 3 ways:
- Have them enter their request in the form at the bottom of the data connectors page.
- Have the customer enter a wish in the external wishlist. (Current list of external wishes tagged with 'data access')
- You can enter a request for the customer in the internal wishlist. Make sure to tag the customer so we know exactly where this request is coming from.
