In today’s fast-changing digital world, businesses are moving from traditional on-premise data solutions to cloud-based platforms. This shift offers many benefits, such as greater flexibility, lower costs, and easier scaling. Informatica, a leader in enterprise data management, provides a powerful cloud-based Master Data Management (MDM) platform to meet this growing demand. Moving from Informatica MDM On-Premise to Informatica MDM Cloud SaaS opens new opportunities for businesses, but it requires proper planning and execution.

In this article, we’ll dive into two important aspects of Informatica MDM Cloud SaaS: the role of indexes in improving data performance and the steps to verify data load accuracy.

What is the use of Indexes in cloud SaaS?

Indexes in Informatica Cloud SaaS enhance data retrieval and search performance by enabling the database to quickly locate specific records without scanning the entire dataset. They play a crucial role in optimizing query execution, batch job performance, and search operations.

Key Benefits of Indexing in Informatica Cloud SaaS

1.  Enhanced Query Performance

• Indexes improve the speed of queries, particularly when filtering data using the WHERE clause.
• They reduce the need for full table scans, allowing the database to access data efficiently.

2. Faster Data Retrieval

• By providing a structured path to locate records, indexes enable quick data access.
• This is especially useful for large datasets where retrieval speed is critical.

3. Optimized Search Operations

• Indexes help optimize search functionality, improving the performance of lookups in large datasets.

4. Custom and System Indexes

• Custom Indexes: Users can create indexes on specific columns to enhance performance for batch jobs and API requests.
• System Indexes: Automatically created for primary keys and unique columns to ensure data integrity and fast retrieval

5. Batch Job Optimization

• Informatica Cloud SaaS can drop and recreate system and custom indexes to optimize batch job execution.

6.  Indexing for Search and Matching

• When using Search Query SIF API, indexing on relevant columns enhances search speed.
• In MDM SaaS, indexes generate tokens for records, helping with the match process to identify duplicates and determine survivorship.

How we can verify the Data Load of a File in MDM SaaS, Mention all the steps.

Verifying data load:

A Master Data Management (MDM) SaaS system typically involves several key steps. These ensure that the data is accurately and fully loaded and that it meets the required quality standards. Here's how you can go about verifying data load in such a system:

1. Check Data Load Status:

MDM Dashboard or Monitoring Tool: Most MDM SaaS solutions provide a dashboard or monitoring tool where you can track the status of data loads. Look for indicators that show if the load process has been completed successfully or if any errors have occurred.

2. Validate Data Integrity:

• Data Counts: Compare the number of records loaded to the expected number. If you're expecting a certain number of records, ensure that the loaded data matches or is within an acceptable range.
• Data Consistency: Check whether the data is consistent across different sources and tables. Look for duplicates, missing fields, or inconsistencies (such as mismatched values) after loading.
• Data Quality Checks: Run data quality reports to ensure that the loaded data adheres to the required standards. These checks can include validation of data types, ranges, mandatory fields, and more.

3. Monitor for Data Availability:

Ensure that the data is available to downstream systems or users. This can include checking if the data is accessible via APIs if reports are being generated correctly, and if any other applications that depend on this data are functioning as expected.

4. Check for Data Errors and Reprocess:

If there are errors in the load, many MDM SaaS platforms allow you to reprocess the failed records or reload the entire dataset. This step may involve:

• Re-running the Data Load Process:

If errors are due to data issues (such as missing values or constraint violations), resolve the issues and reload the data.

• Fixing Data Issues:

Address any data problems such as incorrect formatting, data type mismatches, or integrity constraints.

5. Cross-Check with Source Data:

Ensure that the loaded data matches the source file by comparing sample records. This can be done either manually or via automated data comparison tools. If you're using an MDM system with data governance and version control, ensure that the records are the correct version from the source system.

6. Check for Data Transformation:

If the data was transformed during the load process (for example, through mapping, cleaning, or standardizing), ensure that the transformation rules were applied correctly and that no important data was lost or altered incorrectly.

7. Monitor Performance and System Load:

For large data loads, monitor system performance to ensure that the load process did not cause any resource constraints or timeouts. Check for any performance-related issues that might have affected the data load.

8. Data Reconciliation:

Perform data reconciliation by comparing the loaded data with the source system, ensuring that there’s no data loss or discrepancies. This is important when dealing with complex or large datasets.

9. Verify Data in the MDM Interfaces:

Review the loaded data in the MDM (e.g., Data Stewards, Business Analysts, or through User Interfaces).

Check if the data appears as expected and is properly displayed in the interfaces where it will be consumed.

Conclusion:

Verifying data load in MDM SaaS systems involves checking for successful completion, data consistency, and quality, and performing post-load validation. Leveraging system logs, automated validation tools, and manual checks ensures data is accurately loaded and aligns with the business needs.

By leveraging Informatica’s powerful tools and following the steps outlined above, you can efficiently manage data indexing and verify data loads, ensuring accuracy and optimizing performance in the cloud environment.

Contact us