The way we work has changed, with remote teams now a common part of the landscape. While remote work offers flexibility, it also brings challenges.… Read More »Data-driven insights: Improving remote team performance with time-tracking analytics
Data Lifecycle Management
Data Lifecycle Management focuses on data governance, data cleansing and quality, and data stewardship. The rubric applies to articles that focus primarily on the high-level preparation, flow, and use of data through an organization, rather than with one single facet such as storage or analysis.
Introduction Dear Data Engineers, this article is a very interesting topic. Let me give some flashback; a few years ago, someone in the discussion coined… Read More »Understand the ACID and BASE in modern data engineering
The convergence of Oracle Cloud Infrastructure (OCI) and Hitachi Application Reliability Centers (HARC) to magnify outcomes for customers. Tech giants Oracle and Hitachi Vantara are… Read More »DSC Webinar Series: OCI & HARC: Modernizing Workloads in the Oracle Cloud
Hello, data enthusiast! In this article let’s discuss “Data Modelling” right from the traditional and classical ways and aligning to today’s digital way, especially for… Read More »Data modeling techniques in modern data warehouse
Image Source: Author Introduction Data Engineers and Data Scientists need data for their Day-to-Day job. Of course, It could be for Data Analytics, Data Prediction, Data… Read More »A Detailed Guide for Data Handling Techniques in Data Science
Cloud computing services have grown in popularity significantly over the years. Many sectors are moving to cloud computing services for business operations. Cloud computing enables businesses to store, manage, and process essential data using remote servers hosted on the internet.
Companies need to collect huge volumes of data produced to extract valuable insights via data analysis to survive, let alone thrive in the competitive marketplace. It is the lifeblood of most business decisions, functions, and processes. But the process of data collection can be highly challenging for many organizations.
Trustable data can be defined as data that comes from specific and trusted sources and is used according to its intended use. It is delivered in the appropriate format and time frames for specific users.