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Shadow IT vs. Central IT: Who’s the Winner?

A marketing executive walked into her organization’s IT group and told the first person she saw that she needed help. All she wanted, she said, was to export her WordPress site’s subscriber data into an Excel spreadsheet. Simple. That task wasn’t simple at all, not with the scripts someone in her business unit had his […]
By Ted Cuzillo
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Data and Analytics Trends for 2023

The global big data analytics market is expected to reach $68.09 billion in annual revenue by 2025. It has become one of the most compelling technology trends reshaping business processes and operations. The category is now a crucial resource for both the public and private sectors, as well as for the healthcare industry. Organizations can […]
By Ted Cuzillo
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What Is a Data Lake?

A data lake is a centralized repository where you store structured or unstructured data without having to transform it first. In other words, you simply store it as-is and use it for data analysis. You can store any type or volume of data in full fidelity, whether the data comes from on-premises, cloud, or edge-computing […]
By Ted Cuzillo
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What Is a Data Warehouse?

When it comes to Business Intelligence (BI) products, most of the reporting tools in the space presume that your organization has a data warehouse in place. A data warehouse is most commonly a relational database with data ingested from transactional systems (also known as online transaction processing, or OLTP, systems) on a regular cadence or […]
By Joseph D'Antoni
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Artificial Intelligence vs. Machine Learning: Exploring the Differences

Artificial intelligence (AI) and machine learning (ML) are constantly being used interchangeably in the tech landscape. But are they the same thing? The answer is No. They both combine machines with the study of cognitive science in an attempt to mimick how the human brain performs thought, learning, and mental calculations. However, they have distinct […]
By Joseph D'Antoni
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What Does a Modern Data Stack or Data Structure Look Like?

The traditional data analytics architecture was pretty straightforward—organizations had a number of operational databases, which were nearly always relational databases, with the occasional file share. An extract, transform, and load (ETL) process would sweep data from those systems as part of a batch process. The batch would typically run overnight, but in some cases more […]
By Joseph D'Antoni
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Building a Self-Service Business Intelligence Architecture

Self-service business intelligence (SSBI) has long been the holy grail of data warehouse architectures. Many business intelligence software vendors like Tableau, Qlik, and Microsoft (Power BI) like to make SSBI appear to be as easy as getting data into a data model and handing it off to business analysts. The reality is that delivering a […]
By Joseph D'Antoni
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