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How IBM HR leverages IBM Watson® Knowledge Catalog to improve data quality and deliver superior talent insights

IBM Journey to AI blog

Despite this solution’s ability to effectively ingest data and deliver insights to HR and other IBM business units, addressing data quality and reducing manual checks of the data, which can be labor-intensive and error-prone, remained a challenge. What is data quality? If so, what caused this spike?

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Data architecture strategy for data quality

IBM Journey to AI blog

Both approaches were typically monolithic and centralized architectures organized around mechanical functions of data ingestion, processing, cleansing, aggregation, and serving. Taking an inventory of existing data assets and mapping current data flows. As previously mentioned, a data fabric is one such architecture.

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How Can The Adoption of a Data Platform Simplify Data Governance For An Organization?

Pickl AI

Relying on a credible Data Governance platform is paramount to seamlessly implementing Data Governance policies. These platforms are centralized and designed to manage data practices, facilitate collaboration among different stakeholders, and automate the Data Governance workflow. The same applies to data.

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Comparing Tools For Data Processing Pipelines

The MLOps Blog

As the volume of data keeps increasing at an accelerated rate, these data tasks become arduous in no time leading to an extensive need for automation. This is what data processing pipelines do for you. Data Transformation : Putting data in a standard format post cleaning and validation steps.

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Unlocking the 12 Ways to Improve Data Quality

Pickl AI

This includes removing duplicates, correcting typos, and standardizing data formats. It forms the bedrock of data quality improvement. Implement Data Validation Rules To maintain data integrity, establish strict validation rules. This ensures that the data entered meets predefined criteria.

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Principal Financial Group uses AWS Post Call Analytics solution to extract omnichannel customer insights

AWS Machine Learning Blog

In this post, we demonstrate how data aggregated within the AWS CCI Post Call Analytics solution allowed Principal to gain visibility into their contact center interactions, better understand the customer journey, and improve the overall experience between contact channels while also maintaining data integrity and security.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

Core features of end-to-end MLOps platforms End-to-end MLOps platforms combine a wide range of essential capabilities and tools, which should include: Data management and preprocessing : Provide capabilities for data ingestion, storage, and preprocessing, allowing you to efficiently manage and prepare data for training and evaluation.