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
The conversation around data preparation has been evolving. What started as a push for self-service access for specific use cases has now expanded to operationalizing a data pipeline across the enterprise. The goal is to create efficiencies and eliminate workflow silos to propel data strategy
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
In my last blog post, I explained why businesses need product information management (PIM). I will now dive deeper into the key factors an organization must take into consideration when evaluating a PIM solution. Note that I am not going to cover anything about catalog, hierarchy, category
The best data catalogs can automate the process to collect, classify and profile data to ensure the highest standards of quality. Here are three popular use cases detailing why companies are moving towards IBM’s Watson Knowledge Catalog.
How much time do your data scientists and business analysts spend looking for the right data? How much time do they spend preparing data? And how much time is wasted because they don’t know how trustworthy the data they find is; they find several people have unknowingly spent time looking for the
Does your company have a single source of truth for your business’ most important data? Then it’s time to learn why you need to invest in product information management.
Product information management (PIM) is a subset of the overarching Master Data Management (MDM) space, and it’s primary use is
Nearly every business is under competitive, disruptive, and regulatory pressures. As companies face digital transformation and modernization to meet their customers’ expectations, leveraging data and AI at the speed of business can be the biggest differentiator.
However, according to MIT Sloan, 81
While data is an enterprise’s most valuable resource when it comes to gaining competitive advantage and improving business performance, time is a critical component. Businesses run 24x7, tasking our data citizens to maximize actionable insights that will drive the actions of tomorrow.
Financial services organizations face considerable challenges today. From regulatory changes to globalization to shifting customer expectations, the urgent need to re-engineer outdated systems to better manage vast amount of data can apply additional pressure. Organizations must deal with the