As companies look for ways to use their data to find new opportunities, the importance of real-time insights is growing. But many companies still rely on older, slower approaches to Data Management that struggle to keep up with the pace of business today. Companies know they need better ways to manage data without slowing down […]
How to Overcome the Plateau of Data Analytics Advancement in Today’s Data Overload
The last few years have seen an astronomical increase in the amount of data being created, stored, and shared. According to the IDC, 64.2 zettabytes of data were created or replicated in 2020 largely due to the dramatic increase in the number of people staying home for work, school, and entertainment. The firm also projects the […]
Trends in Data Architecture
What role have Data Management and Data Architecture played in data-driven organizations, especially during the tumultuous and uncertain period at the beginning of the COVID-19 pandemic? Industry thought leader Donna Burbank, the Managing Director of Global Data Strategy, discussed these issues in her presentation Trends in Data Architecture at DATAVERSITY®’s Data Architecture Online conference last July. Burbank shared insights from a 2020 […]
How Can Unifying Data Fabric and Data Management Help Enterprises?
Today, one of the most cutting-edge technologies is data fabric. Data fabric and data management can significantly improve business functions by connecting siloed data and making it accessible across divisions and workgroups. Utilizing a specialized architecture, on-premises data can be shared across multi-cloud and deliver unique insights unavailable with other data management techniques. In this […]
Challenges of Data Governance in a Multi-Cloud World
Today, it would be really hard to find a business totally free of cloud services. In spite of battling centralized “no-cloud” policies in some enterprises, individual departments, work groups, and units are increasingly subscribing to services for data storage and backup, media services, CRM, hosted analytics, and more. Even developers are using Infrastructure-as-a-Service (IaaS) and […]
Data Architecture Challenges
The more your business grows, the more complex your business’s Data Architecture becomes. Enterprise Data Architecture challenges abound – from the beginning and throughout the journey. Data has now become the lifeblood of any business, and business data cannot survive without a solid underlying Data Architecture. Data helps businesses to identify risks and opportunities, understand […]
Data Mesh vs. Data Lake: Which Is Better for Your Business?
In a data-driven business climate, data is playing a key role in capturing market intelligence and “actionable insights” to augment business operations. Thus, Data Management platforms, tools, and associated technologies are increasingly getting a global focus. Two Data Management technologies have created controversies and have become the topic of hot debates: the data lake and […]
DataOps: What It Is and What the Enterprise Gets Wrong
By 2025, the total amount of data created, captured, copied, and consumed globally is projected to reach more than 180 zettabytes. With this rapid growth, the ability to harness data for business impact is even more vital. To keep up with the exponential data growth and resulting challenges, data teams must adjust the way they operate. […]
Aligning Data Architecture and Data Strategy
Peter Aiken disagrees with the popular idea that it’s impossible to put a dollar value on Data Architecture. “It won’t be the right number, but it will be at least a dollar value on it, and if there’s money involved, people should be paying attention to it.” Aiken is an author, Professor of Information Systems, […]
The Evolution of Data Virtualization: From Data Integration to Data Management
Data virtualization was first introduced two decades ago. Since then, the technology has evolved considerably, and the data virtualization of yesterday bears little resemblance to the data virtualization of today. This is due to several facts beginning with the limitations of legacy infrastructure, the massive amounts of structured and unstructured data that organizations were collecting, […]