This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
Noting that companies pursued bold experiments in 2024 driven by generative AI and other emerging technologies, the research and advisory firm predicts a pivot to realizing value. Forrester predicts a reset is looming despite the enthusiasm for AI-driven transformations.
As regulatory scrutiny, investor expectations, and consumer demand for environmental, social and governance (ESG) accountability intensify, organizations must leverage data to drive their sustainability initiatives. However, embedding ESG into an enterprise data strategy doesnt have to start as a C-suite directive.
Corporations are generating unprecedented volumes of data, especially in industries such as telecom and financial services industries (FSI). However, not all these organizations will be successful in using data to drive business value and increase profits. Read on to be sure you set yourself up for success. .
Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.
In light of recent, high-profile data breaches, it’s past-time we re-examined strategic data governance and its role in managing regulatory requirements. for alleged violations of the European Union’s General Data Protection Regulation (GDPR). Complexity. Five Steps to GDPR/CCPA Compliance.
In the final part of this three-part series, we’ll explore ho w data mesh bolsters performance and helps organizations and data teams work more effectively. Usually, organizations will combine different domain topologies, depending on the trade-offs, and choose to focus on specific aspects of data mesh.
According to the MIT Technology Review Insights Survey, an enterprise data strategy supports vital businessobjectives including expanding sales, improving operational efficiency, and reducing time to market. The problem is today, just 13% of organizations excel at delivering on their data strategy.
In our last blog , we delved into the seven most prevalent data challenges that can be addressed with effective data governance. Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture. Don’t try to do everything at once!
These circumstances have induced uncertainty across our entire business value chain,” says Venkat Gopalan, chief digital, data and technology officer, Belcorp. “As The R&D laboratories produced large volumes of unstructured data, which were stored in various formats, making it difficult to access and trace.
Adding another position may not be terribly appealing, but there is one C-suite role every company should consider—chief data and analytics officer (CDO or CDAO). The CDO is an essential role in a data-driven organization. Without a data champion, the C-suite can overlook and even ignore data.
The rise of data strategy. There’s a renewed interest in reflecting on what can and should be done with data, how to accomplish those goals and how to check for data strategy alignment with businessobjectives. The evolution of a multi-everything landscape, and what that means for data strategy.
In the past year, businesses who doubled down on digital transformation during the pandemic saw their efforts coming to fruition in the form of cost savings and more streamlined data management. Here are three key trends that will likely dominate the priorities of APAC’s business leaders in the coming year.
Without a doubt, Artificial Intelligence (AI) is revolutionizing businesses, with Australia’s AI spending expected to hit $6.4 However, according to The State of Enterprise AI and Modern DataArchitecture report, while 88% of enterprises adopt AI, many still lack the data infrastructure and team skilling to fully reap its benefits.
When knowledge workers leave the company, businesses face another challenge—finding a way to document, share and retain their knowledge to extend its benefits throughout the company. Knowledge workers can use them to quickly gather information about a topic, search for solutions to business problems and flesh out innovative ideas.
In 2024, business intelligence (BI) software has undergone significant advancements, revolutionizing data management and decision-making processes. These tools empower organizations to glean valuable insights from their data, enhancing decision-making processes and bolstering competitiveness in data-driven markets.
This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges.
A closer look at the importance (and transformational value) of your organisation’s data landscape. After decades in the background, data is currently king of the business world. What is a data landscape? The definition of data landscape differs depending on the context and who you ask.
While EA leaders have long been positioned as key enablers of digital transformation, the rapidly shifting business landscape of 2025 presents new pressures. Economic uncertainty, geopolitical instability, and the explosion of AI-driven initiatives mean that enterprise architects must redefine their roles to remain relevant and valuable.
We organize all of the trending information in your field so you don't have to. Join 42,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content