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 […]
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 […]
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 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 […]
Metadata Governance: Crucial to Managing IoT
The Internet of Things (IoT), devices that produce and consume data through the internet, will likely comprise over 207 billion devices by the end of 2024. These widgets generate, consume, and send vast data over business networks. As a result, organizations must include IoT in their Data Governance programs to ensure better integration and legal compliance. Without effective governance, firms […]
How to Become a Data Engineer
The work of data engineers is extremely technical. They are responsible for designing and maintaining the architecture of data systems, which incorporates concepts ranging from analytic infrastructures to data warehouses. A data engineer needs to have a solid understanding of commonly used scripting languages and is expected to support the steady evolution of improved Data Quality, […]
A Brief History of Generative AI
Generative AI has a fairly short history, with the technology being initially introduced during the 1960s, in the form of chatbots. It is a form of artificial intelligence that can currently produce high-quality text, images, videos, audio, and synthetic data in seconds. However, it wasn’t until 2014, when the concept of the generative adversarial network […]
The Impact of Data Silos (and How to Prevent Them)
Data silos often develop unintentionally within businesses, catching leaders by surprise. They hinder cross-departmental collaboration while giving rise to inconsistent data quality, communication gaps, reduced visibility, and increased expenses. The gravity of impact can be gauged from a report by Forrester research, which finds that knowledge workers spend an average of 12 hours a week “chasing data.” […]