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Sometimes as data scientists, we are often so determined to build a perfect model that we can unintentionally include human bias into our models. Often the bias creeps in through training data and then is amplified and embedded in the model. If such model enters a production cycle it can have some serious implications directed by …
Read more “3 new steps in the data mining process to ensure trustworthy AI”
Like countless other industries and departments, customer support has undergone a massive transformation. Today I am excited to share more about how IBM is expanding its collaboration with NICE, launching a new integration that allows users to connect AI-powered virtual agents with their call center in a matter of minutes. It sounds funny to talk …
Data is everywhere. It grows exponentially year by year, and it is our duty to keep up with its overwhelming volume and complexity. The thing is, we’re so focused on conquering our data that we often forget this battle to understand it has been one we’ve been fighting since the beginning of time. However, we’ve …
Metadata enrichment is about scaling the onboarding of new data into a governed data landscape by taking data and applying the appropriate business terms, data classes and quality assessments so it can be discovered, governed and utilized effectively. This feature significantly increases the productivity of the data stewards who provide business context to data by …
Read more “Metadata enrichment – highly scalable data classification and data discovery”
Today, most enterprises use services from more than one Cloud Service Provider (CSP). Getting operational visibility across all vendors is a common pain point for clients. Further, modern architecture such as a microservices architecture introduces additional operational complexity. Figure 1 Hybrid Multicloud and Complexity Evolution Traditionally this calls for more manpower. But this traditional approach …
Read more “AIOps reimagines hybrid multicloud platform operations”
In older civilizations, where transportation and communication were primitive, the marketplace was where people came to buy and sell products. This was the only way to know what was on offer and who needed it. Modern-day enterprises face a similar situation regarding data assets. On one side there is a need for data. Businesses ask: …
Read more “Data fabric marketplace: The heart of data economy”
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Data is everywhere in a hybrid and multi-cloud world. Enterprises now have more data, more data tools, and more people involved in data consumption. This data proliferation has made it harder than ever before to trust your data: knowing where it came from, how it has changed, and who is using it. Data provenance is …