You may not be an analytics expert and you may find terms like PMML integration somewhat daunting. But, in reality, the concept is not complex, and the value is outstanding. So, what is PMML integration? PMML stands for “predictive model markup language.” It is an interchange format that provides a method by which analytical applications and […]
Enhancing the Reliability of Predictive Analytics Models
Predictive analytics is a branch of analytics that identifies the likelihood of future outcomes based on historical data. The goal is to provide the best assessment of what will happen in the future. Basically, predictive analytics answers the question “What will happen?” The value of predictive analytics lies in enabling business enterprises to proactively anticipate […]
The Future of Insurance: A Business Analyst’s Insight into Emerging Trends and Technologies
The insurance industry is undergoing a revolution, mainly driven by the application of advanced emerging technologies. The application and installation of new technologies enable a better future for our industry, where customers will receive maximum efficiency, security, and flexibility. Here, we address the major technologies and trends that influence this transition, shedding light on their […]
Demystifying Advanced Analytics: Which Approach Should Marketers Take?
“Advanced analytics” has been the new buzzword on every organization’s mind for the past several years. Recent advancements in machine learning have promised to optimize every arm of an organization – from marketing and sales to supply-chain operations. For some, investments in advanced analytics have been worth the hype. Those who succeed can gain a […]
Mind the Gap: Analytics Architecture Stuck in the 1990s
Welcome to the latest edition of Mind the Gap, a monthly column exploring practical approaches for improving data understanding and data utilization (and whatever else seems interesting enough to share). Last month, we explored the data chasm. This month, we’ll look at analytics architecture. From day one, data warehouses and their offspring – data marts, operational […]
Securing Data in Transit for Analytics Operations
Most enterprises today store and process vast amounts of data from various sources within a centralized repository known as a data warehouse or data lake, where they can analyze it with advanced analytics tools to generate critical business insights. Modern data warehouse platforms such as Snowflake, AWS Redshift, Azure Synapse Analytics, and IBM Db2 are built with […]
Demystifying AI: What Is AI and What Is Not AI?
In recent months, particularly following the release of ChatGPT, there has been an unprecedented surge in interest surrounding artificial intelligence (AI). This heightened attention spans across a multitude of sectors, including business enterprises, technology companies, venture capital firms, universities, governments, media outlets, and more. As the interest in AI is intensifying, some companies have even […]
Beyond the Basics: Advanced Tips for Effective Data Extraction
Data extraction is a cornerstone in data analytics, enabling organizations to extract valuable insights from raw data. While basic extraction techniques are fundamental, understanding advanced strategies is crucial for maximizing efficiency and accuracy. This article will explore advanced tips for effective data extraction, shedding light on automation tools, leveraging APIs and web scraping techniques, enhancing […]
Data Intelligence: The Key to Empowered People and Decisions
McKinsey analysts predict that enterprise employees will rely on data for almost every decision come 2025. If true, this development would mark a significant departure from the current business modus operandi. According to our research, only 25% of enterprise data professionals believe their organization’s decision-making process is data-backed or strategic. How are these two concepts – the perception of data […]
Granularity Is the True Data Advantage
Commerce today runs on data – guiding product development, improving operational efficiency, and personalizing the customer experience. However, many organizations fall into the trap of thinking that more data means more sales, when these two factors aren’t directly correlated. Often, executives will become overzealous in their digital transformations and cut blank checks for data collection, […]