Common Types of Cloud Computing

Before the cloud era, businesses had to rely on in-house data centers and internal hardware and software infrastructures to conduct online business. Organizations had to make substantial investments to set up their websites and networks. Additionally, each business had to hire the right people to manage and monitor their infrastructures. This approach not only added to the […]

Controlling SAP HANA Data Sprawl

Enterprises running large SAP HANA instances in the cloud are seeing a new challenge appear as their databases continue to grow. Since SAP HANA has a simplified data layout and structure compared to a more complex legacy database, it was assumed this would result in less data sprawl and duplication. But does the data stay […]

Modeling Modern Knowledge Graphs

In the buzzing world of data architectures, one term seems to unite some previously contending buzzy paradigms. That term is “knowledge graphs.”  In this post, we will dive into the scope of knowledge graphs, which is maturing as we speak. First, let us look back. “Knowledge graph” is not a new term; see for yourself […]

Spark vs. Flink: Key Differences and How to Choose

Apache Spark is an open-source, distributed computing system that provides a fast and scalable framework for big data processing and analytics. The Spark architecture is designed to handle data processing tasks across large clusters of computers, offering fault tolerance, parallel processing, and in-memory data storage capabilities.  Spark supports various programming languages, such as Python (via […]

A Brief History of the Data Warehouse

A data warehouse stores data from in-house systems and various outside sources. Data warehouses are designed to support the decision-making process through data collection, consolidation, analytics, and research. They can be used in analyzing a specific subject area, such as “sales,” and are an important part of modern business intelligence. The architecture for data warehouses was […]

Leveraging Data Stream Processing to Improve Real-Time Data Analysis 

Data stream processing is rapidly emerging as a critical technology for modernizing enterprise applications and improving real-time data analysis for data-driven applications. As businesses become more reliant on real-time data analysis, data stream processing enables them to analyze and process large amounts of data in real time, providing timely insights and enabling informed decision-making. Traditionally, […]

Types of Databases and Their Uses

There are several types of databases, and their differing designs process data in different ways. Providing access to information is the primary purpose of a database. They can be used for a variety of tasks, ranging from storing photos to buying items online to analyzing marketing and sales data. Large amounts of information can be […]

Is Low-Code and No-Code Development the Solution to Your Productivity Dilemma?

Enterprises’ growing need for quality Data Management and productivity tools has led to an explosion of interest in emerging technologies, such as low-code and no-code platforms, to accelerate their digital transformation objectives. Businesses encumbered by legacy infrastructure must make significant investments and decide whether to buy their technology or build it internally. With both options, fast assembly […]