In-app analysis

Analyze Raw Data assets in-platform using filters, summary stats, grouping, and custom boundaries.

Use In-app analysis to explore Raw Data assets without downloading them. You can filter records, calculate summary statistics, compare groups, and export your work directly in Data Midsouth.

Using the "Query" Feature

Start with the Data tab to preview fields before running a query. In-app analysis is available for Data assets only.

You've chosen a raw data asset from the DMS Catalog. Now what?

Data Midsouth allows you to make calculations and analyze data sets for quick trends within the platform. These options are available in the "Explore by Query" menu. You can adjust which records are included in your calculations using the Filter Pane in the far-left panel.

Go to "Explore by Query"

1

Click "Explore Data" button

This black button is located in the top right corner of the data asset page.

2

Locate and click "Explore by query" tab

The "Explore Data" page offers several ways to interact with raw data assets in the portal:

• Data tab: table view

  • Search or filter for specific records or categories within a single dataset.

• Map tab: map view*

  • Limit records within a single dataset to view on a map

  • *The map feature is limited to datasets that contain geospatial variables like points or boundaries.

• Schema tab: data dictionary view

  • Review the definition of each column in selected dataset

• Explore by Query tab: calculations view

  • Calculate basic stats, apply filters, and aggregate data

Calculate One Overall Stat

[Need quick intro here]

1

Select a Function

Start by selecting a math function you want to analyze - like count, average, or sum - from the drop down.

2

Select a Field

Choose the Field (or column name) you want to analyze from the dropdown.

For example: "Building Permit Cost"

3

Click confirm

Selecting confirm will calculate the statistic you're interested in, such as "The average building permit cost in Shelby County."

4

(Optional) Filter Pane

Making selections on the Filter Pane (lefthand side) will further narrow which records to include in the calculation.

For example, the average building permit cost in the 38103 zip code.

You will see your selections under "Refine."

Calculate stat for categories or groups

1

Follow the steps for calculating an overall step

Listed above.

2

Scroll down to Group By section

3

Choose a category to Group by

Categories could include:

• Geographic areas, like Zipcodes or City Council districts

  • Allows you to compare a statistic across areas. For example, the average building permit cost by zip code

• Different kinds of something, like land uses or permit types

4

Select Confirm button

Advanced Filtering with WHERE

To narrow down your dataset by a text string like "Contains" or filter to values greater or less than a specific number, you need to use the WHERE function.

1

Scroll to WHERE section

2

Select a field

Choose the Field (or column name) you want to analyze from the dropdown.

3

Select an operator

Operators act as filters that limit the results. Some are more sensitive and some are more broad. It's important to keep this in mind depending on the type of results you're expecting.

ANY FILTER

• contains / does not contain: Finds records where a field includes (or excludes) specific keywords or characters—even if they're part of a larger word or phrase.

  • Example: Permit description contains "shed" → returns "shed," "watershed," "storage shed addition"

  • Example: Permit description does not contain "pool" → excludes any record mentioning "pool"

• equal to / not equal to: Finds records where a field exactly matches (or doesn't match) a specific value. This is stricter than "contains" because the entire field must match.

  • Example: Status equal to "Approved" → returns only records where the status is exactly "Approved"

  • Example: City not equal to "Memphis" → excludes records where the city is exactly "Memphis"

• is empty / is not empty: Finds records where a field has no value (is blank) or has any value at all.

  • Example: Date is empty → returns records missing a date

  • Example: Email is not empty → returns only records that have an email address

DATE FILTER

• strictly prior to / strictly post: Finds records before or after a specific date, not including that date.

  • Example: Issue date strictly prior to 01/01/2024 → returns records from December 31, 2023 and earlier

  • Example: Issue date strictly post 01/01/2024 → returns records from January 2, 2024 and later

• prior or equal to / post or equal to: Finds records before/after a specific date, including that date.

  • Example: Issue date prior or equal to 01/01/2024 → returns records from January 1, 2024 and earlier

  • Example: Issue date post or equal to 01/01/2024 → returns records from January 1, 2024 and later

NUMBER FILTER

• strictly superior to / strictly inferior to: Finds records where a number is greater than or less than a specific value, not including that value.

  • Example: Square footage strictly superior to 1000 → returns 1001 and up (not 1000)

  • Example: Permit fee strictly inferior to 500 → returns 499 and below (not 500)

• superior or equal to / inferior or equal to: Finds records where a number is greater/less than or exactly equal to a specific value.

  • Example: Square footage superior or equal to 1000 → returns 1000 and up

  • Example: Permit fee inferior or equal to 500 → returns 500 and below

Quick Reference: Which Operator Should I Use?

[add in decision tree or other support]

Tip: Not sure whether to include the boundary value (the exact date or number you're filtering by)? Use the "strictly" versions to exclude it, or the "or equal to" versions to include it.

Export results

1

Scroll down to Export section

It should be located beneath the WHERE section.

2

Click a format

The results are available in several formats, including CSV, JSON, or Excel.

See Downloads & formatsfor more information about each type.