Retaining customers is a high priority and a constant challenge for businesses. Today’s customers expect frictionless and consistent experiences across all channels. They also expect you to anticipate and meet their needs. If you don’t, they are likely to switch to a competitor. Likewise, if you miss market trends, which can change incredibly fast,…
Modern automotive customers expect engaged and superb user experiences. Automotive companies can collect, store, and analyze data across a spectrum of assets. By architecting better customer experiences (CX), automotive companies will reduce customer churn and increase new vehicle sales. Intelligent Vehicles Connected cars, beginning with the GM OnStar service, provided the world an early…
As organizations seek to capitalize on Generative AI (Gen AI) capabilities, data scientists, engineers, and IT leaders need to follow best practices and use the right data platform to deliver the most value and achieve desired outcomes. While many best practices are still evolving Gen AI is in its infancy. Granted, with Gen AI,…
As the Vice President of Engineering at Actian, I have been very involved in the recent launch of our Actian Data Platform. My role in this major upgrade has been twofold—to ensure our easy-to-use platform offers rewarding user experiences, and to deliver the technology updates needed to meet our customers’ diverse data needs. On…
For most companies, a mixture of both on-premises and cloud environments called hybrid cloud is becoming the norm. This is the second blog in a two-part series describing data management strategies that businesses and IT need to be successful in their new hybrid cloud world. The previous post covered hybrid cloud data management, data…
Gartner defines data governance as the specification of decision rights and an accountability framework to ensure the appropriate behavior in the valuation, creation, consumption and control of data and analytics. Data governance is vital to ensure that your data is consistent and trustworthy and doesn't get misused. One of the first steps you’ll need to…
The Data Management Association (DAMA) International defines data governance as the “planning, oversight, and control over management of data and the use of data and data-related sources”. Given this definition, should you view data governance as a necessary compliance chore on your long to-do list or a strategic investment that can grow your organization’s…
Implementing sustainability initiatives is a huge win for manufacturers who are not only helping the environment, but also helping themselves, since sustainability and profitability often go hand in hand. In fact, according to Bank of America Merrill Lynch, firms with a better Environmental, Social and Governance (ESG) track record than their peers produced higher…
Gartner defines data governance as the specification of decision rights and an accountability framework to ensure the appropriate behavior in the valuation, creation, consumption and control of data and analytics. Data governance is vital to ensure that your data is consistent and trustworthy and doesn't get misused. One of the first steps you’ll need to…
Customer journey analytics interprets data from various touchpoints and interactions that a prospect or customer has with a company from end-to-end. Insights into the customer experience, behavior, and points of friction in sales and service help optimize the customer journey to improve customer satisfaction and drive better business outcomes. However, to derive these benefits…
What is an Object-Oriented Database Management System? An object-oriented database management system (OODBMS) is based on the principles of object-oriented programming. Data is created, modeled, and stored as objects, which are self-contained units that contain both data and the operations or methods that can be performed on that data. Should your organization’s enterprise data…
We live in a data-driven world. The amount of data/information generated, gathered, copied, and consumed is forecast to reach 180 zettabytes by 2025. With this rapid expansion comes tremendous opportunities for organizations to gain actionable insights to improve business outcomes. However, to realize the full potential of data, comes the need for effective data…
It may not seem like it, but Artificial Intelligence (AI) has been around for a long time. The earliest successful AI program was written in 1951 by Christopher Strachey who later became director of the Programming Research Group at the University of Oxford. ChatGPT Is a chatbot that uses AI to perform a variety…
A data management strategy is the process of creating a plan to handle the data created, stored, managed, and processed by an organization. This roadmap ensures that data management activities work together effectively and efficiently to meet business goals and objectives. Here are some critical steps for creating a data management strategy along with ways…
The campaign for responsible use of Artificial Intelligence (AI) has grown like a massive wildfire, and the magnitude of the problem is growing faster than authorities can keep up with. Agencies around the world are working to make sense of it all and provide practical solutions for change. For global business leaders, this means…
Driven by the desire for organizations to get better business insights, data systems are becoming more specialized, and data stacks are increasing in complexity. As companies continue their quest toward data-driven operations, they must balance speed and cost. This is why we recently engaged with GigaOm Research to conduct a TPC-H Benchmark Test against…
