ThoughtWorks consultant Zhamak Dehghani created the concept of data mesh as a self-serve, domain-oriented design that later evolved into a data-as-a-product design. By integrating and analyzing data from disconnected systems all at once, the data mesh architecture benefits the organization by eliminating the need to pull data from multiple systems and preprocess it. In a […]
What Is Data Mesh?
Data mesh is a type of organization and architectural paradigm, or – in simpler words – a distributed architecture for Data Management. The goal is to provide accessibility by distributing the data in the way that the end user needs it. It allows teams to embrace a self-serve data architecture design where they can look at data as […]
Five Data and Analytics Trends: What Lies Ahead in 2023
It’s rare, if not impossible, to find a business that does not have a digital presence. The convenience factor of digital is accelerating the pace at which businesses are applying an online presence, including the ones that were mainly brick-and-mortar before COVID. More than just offering products and services in this way, most organizations are […]
The Importance of a Modern Data Architecture
The legacy architecture of some organizations’ data systems may need a serious upgrade to stay competitive. For example, the old architecture of a business may provide a clumsy fit when accessing cloud services and take longer to transfer data and perform tasks within the cloud. This results in higher cloud costs. Additionally, upgrading to a […]
How a Stateless Data Architecture Can Enable You to Harness the Power of Today’s Agile Data
Technologies are sometimes categorized as stateful or stateless. The terms can apply to applications or communication protocols, for example. A stateful application saves data generated by each client session and uses it the next time the client makes a request. A stateless application doesn’t save client data from one session to the next. We can […]
The Hype Around Semantic Layers: How Important Are Standards?
There are several reasons why the notion of semantic layers has reached the forefront of today’s data management conversations. The analyst community is championing the data fabric tenet. The data mesh and data lake house architectures are gaining traction. Data lakes are widely deployed. Even architectural-agnostic business intelligence tooling seeks to harmonize data across sources. Each […]
High-Fidelity, Persistent Data Storage and Replay
In arguably the most iconic scene from Bladerunner, replicant Roy Batty describes his personal memories as “lost in time, like tears in rain.” Until immortality is invented, we’ll have to settle for solving the same problem in data enablement. Actionable data lost to time. How are we still talking about this? With incredible advances in data […]
Data Mesh 101
In today’s complex business environment, data lakes and data warehouses may not be sufficient to meet organizational requirements. From the perspective of agility, both data lakes and data warehouses have limitations when it comes to maintaining and managing various types of data. Enter data mesh. The idea of a data mesh was born when Zhamak Dehghani, the […]
Advances in Metadata Management
With the flood of data that organizations are experiencing, metadata management is no longer optional – it has become a necessity. The concept of metadata management is fairly new because older metadata services, before this rush of data, had no significant problems locating data files. Now they do. Metadata, at its most basic, can be described […]
Data Mesh or Data Mess?
The ways in which we store and manage data have grown exponentially over recent years – and continue to evolve into new paradigms. For much of IT history, though, enterprise data architecture has existed as monolithic, centralized “data lakes.” More recently, as the role of data evolves and changes, so too does where that data […]