IBM Watson Knowledge Catalog (WKC) provides a modern machine learning (ML) catalog for data discovery, data cataloging, data quality, and data governance. Within this framework lies a central Knowledge Catalog that serves as a single source of truth for data engineers, data stewards, data
Imagine opening your mailbox and seeing a letter addressed to “current resident,” or having your financial institution’s AI powered digital assistant inform you that your replacement card is on its way to your old address.
Most people would take this impersonal letter, throw it in the trash, and go
Imagine a day in the life of Sarah, a hypothetical Chief Data Officer at a major bank in South Africa. There are many expectations on her shoulders. She struggles to deliver business-ready data to fuel her organization and support the decision makers within the bank. It is her job to put in place a
DataOps is the orchestration of people, process, and technology to accelerate the quick delivery of high-quality data to data citizens. When done right, DataOps creates business value because users know what data they have, can trust the quality and its meaning, and use it without violating
The expectation to achieve faster results continues to rise. Businesses everywhere are looking for ways to improve their operational efficiency and effectiveness to enable the best decision-making. The need to optimize typically comes to a head with the reality that there are many silos within any
Most businesses collect data but are unable to use it to generate business value or deliver insights in a timely fashion. Data volume and data types continue to grow, as do the different types of data citizens—ranging from business users to data scientists. As a result, data management and delivery
All industries—from healthcare to retail to banking—are digitally transforming themselves every day to become more agile and stay competitive. However, all industries depend on data to be successful, and this impacts the way enterprises plan and execute their operations. Although enterprises have
The number of business segments requiring data to drive contextual insights is increasing. Leaders are seeking new ways to manage the pressures of delivering high-quality data faster across their businesses. To date, many of these projects have focused solely on ingesting data into a data lake
From reading the news headlines of yet another retail chain closing its stores, one can easily be left with the impression that we’re in a retail apocalypse. But in reality, the overall retail industry is very strong and healthy—especially online.
What we’re witnessing however, is a transformation
Let’s say you’re the Chief Technology Officer of a bank or retailer struggling to infuse AI that aims to improve customer experiences. You likely face three main challenges:
Data sprawl: Your customer data is currently on multiple clouds, including on-premises and a cloud data lake storage
Data democratization allows data to be accessed across the organization and empowers individuals to use the data in their decision making and gain critical business insights. Data democratization is fast becoming a game changer as it’s moving towards a user centric micro-services based architecture.
There’s a general need for next-gen executives to not only understand corporate regulations, but be able to adhere to and follow them using metadata solutions like data governance. As the business world’s top asset becomes data, data governance will ensure that data and information being handled is
Managing enterprise information has always been a good idea, however with the potential for looming penalties from the General Data Protection Regulation (GDPR) non-compliance, companies are waking up and some organizations are even seeing GDPR as an opportunity to establish strengthened
Today’s most successful companies think differently about data governance. Recent Aberdeen research suggests that top-performing companies are those that create a more holistic approach to data governance, incorporating the right technologies, processes, skill sets and internal capabilities.
Although there are many new and emerging classes of data integration, quality and governance software tools available in the market, many large organizations are coming to the conclusion that they're best served by a single unified enterprise data integration, quality and governance platform that