Kueri, a natural language database tool - Part Four

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Configure a Kueri Data Source
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After the Kueri login, I clicked Data Sources at the bottom right and on the Data Sources page, I clicked

1. Set up a New Connection to a data source
New Connection. In the MySQL Workbench

2. Find the Cloud SQL IP address
I copied the Cloud SQL IP address from the kueri_demo connection, and back at the Kueri Admin page, I drilled down to open the New Database connection

3. Build a new database connection
page. I named the new Database Connection "kueri_demo"; for the Host, I used the Cloud SQL resource IP address I copied as shown in Figure 2 above. Note that I could have found the IP address at the Google Cloud SQL console as well. I used the Google Cloud SQL credentials for the user name / password, I tested it, and I clicked Next to open this

4. Choose tables
page. Although this page shows a "test_demo_table", the create database script in the GitHub repository file will not create this table and this article will not use this table in any way. It shows on this page only for my own testing and development work. Click Next to open this

5. Initial configuration - Data Source tables
page for initial configuration of the chosen tables. To get the most out of Kueri, table configuration matters the most. The folks at Kueri themselves publish great documentation here and especially here - more than enough to get going. In the GitHub repository, I included the latest schema, or database configuration, for the kueri_demo datasource. Of course, Kueri allows and encourages further datasource data table configuration after the initial work phase. Drill down

6. Configure existing tables
to

     Configure -> Edit

tables to open the table configuration page, and proceed.

A configured Kueri Data Source becomes a valuable resource, and resource owners need a way to backup and restore it. For Kueri, this means "Export / Import a Semantic Map". To do this, drill into the Data Source options

7. Export/Import Semantic Map
of the relevant data source (kueri_demo in this case) and click Export/Import Semantic Map. This dialog box

8. Export / Import dialog box
will open. In the GitHub repository, file

     KUERI_ARTICLE_RESOURCES.zip

 has an exported backup file called

     kueri_demo_30.1

for the kueri_demo Data Source described in this article. To use it, build a basic bare-bones Kueri Data Source called "kueri_demo", and then import kueri_demo_30.1 with the feature described here.

I found that I could handle the table configuration more easily with the Workspace open in one browser tab and the Table Configuration page open in another tab.

Note that web developers can embed Kueri in the web software they build. Although I have not yet explored that feature, it clearly has even more potential.

As I worked with Kueri to configure the

     kueri_demo

Data Source, I realized that the more effort one puts into a Kueri configuration, the more value Kueri will return. The

     kueri_demo_30.1

file reflects my latest configuration work, and because this involved experimentation, a description of this work does not fit well in a review article. I admit: I am still learning how to configure - and more importantly optimize - Data Source tables in and through Kueri. I believe that like so many other products, Kueri will start as a skill set, then grow into a specialty, and finally become an industry. Right now, I am at the Kueri skill set building stage.
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As we've seen, Kueri integrates natural language with relational database resources. It solves a difficult problem and it solves that problem well. Although it has a large configuration space, anyone with a basic understanding of that space can use it. More understanding and skill means more value returned. Kueri has unlimited potential.