The process of data classification can be broadly described as the organization of data into relevant categories, allowing it to be accessed and protected more efficiently. In the simplest terms, the data classification process ranks data based on its security needs and makes it easier to locate and retrieve data. Classification is especially useful to […]
Creating a Data Monetization Strategy
A data monetization strategy is an executable plan for extracting “value” from data and converting it into revenue-generating opportunities. It involves analyzing and leveraging data to uncover insights that can be used to drive business growth, enhance customer experiences, and create new revenue streams. Organizations collect large volumes of raw data from various sources such […]
Graph Databases: Benefits and Best Practices
Graph databases have improved significantly since the 1990s, with new developments and a better realization of best practices. Graph technology has become one of the most popular methods of performing big data research. Its focus on finding relationships and its flexibility make it ideal for a variety of research projects. An awareness of new developments […]
Data Lakehouse Architecture 101
A data lakehouse, in the simplest terms, combines the best functionalities of a data lake and a data warehouse. It offers a unified platform for seamlessly integrating both structured and unstructured data, providing businesses agility, scalability, and flexibility in their data analytics processes. Unlike traditional data warehouses that rely on rigid schemas for organizing and […]
A Brief History of Data Ontology
It can be said that the history of data ontology starts with the development of ontology as a concept in Greece, back in the fourth century B.C.E. It was developed by Aristotle, the famous philosopher. Ontology is a branch of philosophy that is used to classify and explain “that which exists” or answer the question […]
Sustainable Data Management: Trends and Benefits
The rapid growth of digital data has led to a significant environmental impact that cannot be overlooked. Understanding the need for a greener digital landscape and sustainable data management is crucial to mitigate this impact and ensure an eco-friendly future. Data management, including storage, processing, and transmission, requires vast amounts of energy. Additionally, the manufacturing […]
In-Memory Databases: An Overview
In-memory databases work faster than databases with disk storage. This is because they use “internal” optimization algorithms, which are simpler and faster, and this type of system requires fewer CPU instructions than a disk storage system. Additionally, accessing data that has been stored “in-memory” eliminates the need for seek time while searching for data. As […]
Data Warehouse vs. Database
What are data warehouses and databases? How are they different, and when should you use a data warehouse vs. database to store data? Below, we will look at the differences and similarities between them. What Is a Database? In a database, data is presented in a structured manner for easy access and manipulation. Vast amounts […]
Demonstrating the Value of Data Governance
As organizations strive to become more data-driven, they increasingly recognize the importance of Data Governance (DG), a business program supporting harmonized data activities. However, business leaders, colleagues, and workers often express confusion about DG policies and need clarity around its value. This article tackles this issue by exploring the top 10 ways for effectively articulating the value […]
Data Integration Tools
Data integration tools are used to collect data from external (and internal) sources, and to reformat, cleanse, and organize the collected data. The ultimate goal of data integration tools is to combine data from a variety of different sources, and provide their users with a single, standardized flow of data. Use of these tools helps […]