There’s been a lot of talk about semantic layers lately. I’ve seen dozens of companies using a semantic layer to drive self-service analytics at scale. But even with all these success stories, I still get this question: “Is a semantic layer worth the effort?” In other words, is the juice worth the squeeze? So, how […]
How a Modern Cloud Analytics Stack Can Optimize the Value of Your Data
Data is vital when it comes to growing a business, but many organizations fail to utilize it properly once it has been collected. At the same time, many forward-thinking businesses, from startups to large corporations, have implemented a modern cloud analytics stack to use data more efficiently. In this article, we will discuss how a modern […]
Major AI Trends for Traditional Enterprises in 2023
Post-pandemic, the demand for AI is surging, as many organizations ascertain the need for AI to keep pace with the current business landscape in the face of a looming recession. AI can help enterprises improve business processes, increase speed and accuracy, and help make predictions to optimize their performance. In 2023, there will be many ways […]
Data Modeling Trends in 2023: A Refresh
Data Modeling, the practice of diagramming Data Architecture and aligning core business rules with data definitions, will go through a refresh in 2023. Organizations will assess and make over their data fabrics, which describe distributed Data Management systems. Furthermore, managers and project teams will use data models to optimize business processes with their data assets and allocate resources to achieve […]
NoSQL Databases: Advantages and Disadvantages
NoSQL databases (aka non-relational databases) come with both advantages and disadvantages. On the plus side, they are more scalable than traditional relational databases and can store a variety of formats. Additionally, they are easy to use, and their flexibility can speed up development, especially in a cloud computing environment. NoSQL databases were developed as a […]
Data Architecture 101
The term “data architecture” is defined as a set of models, policies, rules, and standards governing data flow and management within an organization. Thus, data architecture, a subset of enterprise architecture, involves the operating rules governing data-related activities like data capture, data storage, data integration, and data usage. In other words, this collection of models, standards, […]
APIs and Data Sharing: Key Challenges to Address
Realizing the full potential of real-time data sharing among partners in an organization’s ecosystem is a crucial component of digital transformation. For digital businesses to progress quickly, it will take more than just better data management and more insightful analysis. All of these endeavors should result in quantifiable gains for the company. According to Gartner, “Data […]
Azure Data Migration: 5 Tools to Know About
With many organizations migrating their critical workloads to cloud environments, choosing the appropriate data migration solutions is increasingly important. Identifying the right tools is a key step in the data migration process. There are several use cases and possible scenarios for a data migration project. For example, you might lift and shift the data from […]
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 […]