feature bg

5 Grounds You Require an Augmented Data Quality Solution Right Now

It's no surprise that manually organizing data quality is a losing war. Whether it's duplicates, misspellings, or poor records, bad data costs companies up to$12.8 million annually.

The fact that bad data costs companies plutocrat is no longer news. Instead, it's just the reality we're all trying to grapple with as both the quantum of data we consume and our dependence on it grows. Augmented data quality technology earns traction

According to Gartner, 60 associations will work AI-enabled data quality technology for suggestions to reduce homemade tasks for data quality enhancement by 2022.

Technology like Octivia Data Solution's Augment uses machine learning to dissect and cover data quality continuously. With Augment, you can fluently identify data quality patterns and dissect data quality's impact on your business models.

The technology is the moment; there's no need to stay until 2022. Then are 6 data quality checks you can and will want to automate ASAP.

1. Absoluteness

Absoluteness flags when essential information is missing. The rule set for absoluteness quests for null values so you can identify if you're missing any pivotal data like fidelity number, billing information, or mailing address.

2. Consistency

There are multiple reasons lines are inconsistent. Whether because of human error or data that's gone wrong, it's prevalent for companies to struggle with data delicacy, especially as they continue to invest further and further data.

Let's say you're an insurance provider that demands to shoot streamlined sequestration information to all Virginia residers following the relinquishment of the Virginia Consumer Data Protection Act (VCDPA). Still, the results really should point to VA, If a stoner quest for Virginia but gets no results. Using review/ regex patterns, Augment can overlook countries to see how numerous countries start with a V and are accurate.

3. Accuracy

Accuracy is grounded on the chance of records falling between the upper and lower limit you choose.

For illustration, if you're a manufacturer and want to measure first pass yield (the chance of completed products that connect specifications/ total products produced), you can enter a lower limit of 92% and an upper limit of 98%.

Still, equaling 85, it's an outlier and impacts data delicacy, If your first access yield falls outside that scope on a single day.

4. Conformity

Conformity implies that data is in the form or structure demanded. For illustration, a date follows MM/ DD/ YY standards. DD/ MM/ YY or MM/ DD/YYYY. However, you'd know more if you'll admit your payload in May or June If you're a global manufacturer and you hold an order for inventories set to be delivered 05/06/22.

Using Augment, you can explore data conformity just by typing the date format you like to search. The tool will manage the SQL rules and will recognize any data that doesn't match your prerequisites. Over time, data integrity can be merged with these rules to signify patterns.

5. Integrity

Data integrity points to the characteristics that determine the trustability of your information. It's grounded on parameters similar to the delicacy and thickness of the data over time. Measures for data integrity include the chance of records distributed as - In Range, Like/ Regex pattern, and Not null.

  • The In Range measure is for numerical columns
  • The Like/ Regex pattern is for textbook columns

They both can't be used to the same column. Still, not null, and In Range or Like/ Regex pattern can be combined.

What does that look like? Let's go back to our Virginia illustration. Say we've 100 records, and 90 include a state's name. Out of those 90, 40 countries start with 'V.' That means our Like pattern is 40 percent and not null is 90 percent. Overall integrity is typical of the two probabilities – 65 percent (40 percent of like) (90 percent of not invalid)/ 2 (no of data quality checks))

Record your data quality checks and let Augment do the work

With Augment, Octivia Data Solution's unified data operation platform, you can set all of these data quality checks formerly and record them to run at regular intervals of your choice. The results are peopled in two dashboards – one for specialized users and one for business users.

Share Now: