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…

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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…

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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…

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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…

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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,…

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The Rise of Augmented Analytics: Combining AI with BI for Enhanced Data Insights

Businesses today are drowning in data. The sheer volume and complexity of information available have made it increasingly difficult for organizations to extract meaningful insights using traditional business intelligence (BI) tools and the expertise of specialized data scientists. This is where augmented analytics comes in. This game-changing technology combines the power of artificial intelligence (AI)…

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Understanding Linear Regression Intercepts in Plain Language

I am often asked about the role of intercepts in linear regression models – especially the negative intercepts. Here is my blog post on that topic in simple words with minimal statistical terms.   Regression models are used to make predictions. The coefficients in the equation define the relationship between each independent variable and the dependent variable….

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Preparing for La Niña: Adopting Predictive Maintenance Before Hurricane Season

With a La Niña watch issued for the summer, businesses operating in hurricane-prone regions face heightened concerns about the impending storm season. La Niña heavily impacts the wind shear and atmospheric conditions over the Atlantic, where most hurricanes form thanks to its warm waters. It’s rare to go a year without a hurricane hitting some part of…

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Overcoming Real-Time Data Integration Challenges to Optimize for Surgical Capacity

In the healthcare industry, surgical capacity management is one of the biggest issues organizations face. Hospitals and surgery centers must be efficient in handling their resources. The margins are too small for waste, and there are too many patients in need of care. Data, particularly real-time data, is an essential asset. But it is only…

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Demystifying Data Analytics Models

In today’s global landscape, organizations worldwide are increasingly turning to data analytics to enhance their business performance. Research conducted by McKinsey Consulting revealed that data-driven companies not only experience above-market growth but also witness EBITDA (Earnings Before Interest, Taxes, Depreciation, and Amortization) increases of up to 25% [1]. Additionally, Forrester’s findings indicate that organizations utilizing…

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