In today’s digital age, businesses are generating vast amounts of data, and storing and analyzing this data has become crucial for businesses to operate effectively. To manage this data, many organizations are turning to cloud infrastructure, specifically multicloud systems. Multicloud, which is the use of multiple cloud services from different providers, promises more flexibility, scalability, and resilience. However, like anything
Oracle Essbase is a powerful multidimensional database that provides users with advanced analytical capabilities, including OLAP (Online Analytical Processing), data mining, and predictive modeling. Oracle Business Intelligence Enterprise Edition (OBIEE) is a comprehensive BI platform that offers a wide range of reporting and analysis features. Together, these two tools provide a formidable combination for advanced reporting and analysis that can
As organizations continue to advance in their data journeys, they often encounter obstacles in utilizing the full benefits. Although technology has aided in surmounting some of these hurdles, it is not always sufficient to enhance business agility, scalability, and time-to-market. In response, decentralized architectures such as data mesh are becoming more popular as more organizations seek solutions to unlock the
Tableau, a leading provider of interactive data visualization software, has announced its second analytics platform update of 2023. The latest update – Tableau 2023.2 – includes more than 20 new features that are now generally available. One of the most significant of these new features is an improved connector to the Salesforce Data Cloud, which promises a more user-friendly interface.
In today’s world, businesses are generating an unprecedented amount of data. This data comes from a variety of sources, including customer interactions, social media, sensors, and more. To make sense of all this information, companies must adopt effective data management principles. Data management refers to the process of organizing, storing, protecting, and maintaining data so that it can be easily
As businesses rely on data to drive decisions, Customer Data Platforms (CDPs) have gained importance in the marketing and data analysis ecosystem in recent years. CDPs serve as a central repository for various types of data, including customer interactions, behaviors, and preferences, enabling businesses to build better customer profiles for personalized engagement. In this article, we will explore the evolution
As data continues to grow at an unprecedented pace, businesses need to find ways to extract insights and generate value from their data assets. The rise of self-service analytics is a testament to this need. With self-service analytics, business users can access and analyze data without assistance or support from IT personnel or data scientists. However, the rise of self-service
Artificial Intelligence (AI) and Machine Learning (ML) are transforming a wide range of industries, from healthcare and finance to retail and logistics. However, the growing reliance on AI algorithms and predictive analytics raises the question of whether these systems can be biased. In this article, we will explore the importance of data in AI, the risks of biased data, and
Metrics have always played an important role in the Human Resources (HR) industry. However, it wasn’t until recently that HR professionals realized the true value of data analytics in understanding employee behavior and its subsequent impact on the overall business. The use of Key Performance Indicators (KPIs) has become essential for HR managers and executives in making informed decisions about
As businesses increasingly rely on data to make decisions, it is becoming imperative that the data driving these decisions is trustworthy. This is where data lineage comes in. Data lineage can be described as a historical map of data’s journey within an organization. It tracks data from its origin to its final destination, capturing changes as the data is processed,
The rise of big data has led to an increase in demand for data analysts, scientists, and engineers. However, to effectively work with data, one has to choose the right programming language that suits their needs and expertise. In this article, we will discuss the best programming languages for data analysts, the most commonly used languages by data scientists, and
The field of human resources has recently undergone a transformation due to the rise of HR analytics. Data-driven decision making has become an essential part of HR operations, and organizations are heavily investing in collecting, storing, and analyzing HR data. However, the increasing complexity of HR analytics tasks and the expanding scope of data privacy laws make protecting HR data
