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Self-Service Analytics: Pros and Cons

Self-service analytics empowers the non-technical users in an organization. Traditionally, data analysis was the domain of specialized data scientists or IT professionals with skills to manipulate and interpret complex datasets. In self-service analytics, user-friendly tools enable ordinary business users to conduct data analyses without expert knowledge or support.   These tools typically feature user-friendly interfaces, drag-and-drop functionalities, and pre-built templates […]

Large Language Models 101

Large language models (LLMs), built on the transformer architecture of deep learning, are designed to process very high volumes of textual data at a high speed. LLMs also have the power to generate new text and interact with human language innovatively. Training on different types of data, including articles, books, periodicals, and websites, LLMs develop […]

Generative AI vs. Traditional AI

Traditional AI, also known as “classical AI,” is known for being rule-based and dependent on stringent programming for its intended output. These techniques revolve around the manipulation of symbols and logical reasoning to perform tasks.  Key methodologies include rule-based systems, where knowledge is encoded in the form of “if-then” statements, enabling machines to make decisions […]

Six Common Digital Transformation Challenges

During digital transformation, one of the most formidable challenges organizations face is resistance to change and the complexities of effective change management. Human nature often gravitates toward familiarity and routine, making any deviation a source of discomfort. This psychological inertia can stem from various factors including fear of job loss, perceived inadequacy in new skill […]

Data Storytelling 101

Humans are inherently wired for stories. Stories captivate our imaginations, simplify complexity, and provide context – and turn abstract figures into relatable scenarios. Data storytelling takes advantage of this human passion.  In data storytelling, the message is conveyed through engaging narratives, making the data insights inspire a high level of trust among the audience. It empowers stakeholders […]

Evaluating Enterprise Data Literacy

Any organization that aims toward complete digital transformation must move toward enterprise data literacy. So, what exactly is data literacy? Gartner defines data literacy as: “The ability to read, write and communicate data in context, including an understanding of data sources and constructs, analytical methods and techniques applied – and the ability to describe the […]

Fundamentals of Descriptive Analytics

In descriptive analytics, data aggregation, and data mining techniques are used to collect and review the historical data of a business to gauge the past performance. The most common example of descriptive analytics is the reports that a user gets from Google Analytics tools. A web server’s summarized performance reports may help the user analyze […]

Implementing Data Fabric: 7 Key Steps

Understanding the importance of data integration is vital in the intricate process of implementing a data fabric. Data fabric architecture aims to create a unified and integrated environment for managing an organization’s data sprawl across various platforms and systems. Within this context, the data integration step ensures disparate data sources are seamlessly connected, enabling a fluid exchange […]

Data Ethics 101

Data ethics ensures that businesses handle data – beginning with its acquisition and ending with its distribution – with full attention to individual rights, privacy, and consent. Moreover, ethical decision-making in businesses has to strike a balance between technology and morality to preserve individual rights.  This includes considerations around transparency, accountability, and fairness in the […]