Automated machine learning (AutoML) is a set of tools and techniques that automate the design, training, and deployment of machine learning models. AutoML has become essential due to the amount of data involved when creating ML models, helping to save a significant amount of time, human resources, and money. Although manual machine learning is not obsolete, automating […]
Data Warehouse vs. Data Lakehouse
The phrase “data warehouse vs. data lakehouse” offers an exciting topic for ongoing debate in the global Data Management world. While businesses have relied on traditional data warehouses for storing structured and semi-structured data for years, the more recent technological solution of the data lakehouse is growing in importance because of its unique ability to provide structure to raw data. […]
Structured vs. Unstructured Data: An Overview
Structured data and unstructured data are both forms of data, but the first uses a single standardized format for storage, and the second does not. Structured data must be appropriately formatted (or reformatted) to provide a standardized data format before being stored, which is not a necessary step when storing unstructured data. The relational database […]
NoSQL Databases: Advantages and Disadvantages
NoSQL databases (aka non-relational databases) come with both advantages and disadvantages. On the plus side, they are more scalable than traditional relational databases and can store a variety of formats. Additionally, they are easy to use, and their flexibility can speed up development, especially in a cloud computing environment. NoSQL databases were developed as a […]
4 Risks of Storing Large Amounts of Unstructured Data
Click to learn more about author Gary Lyng. In 2013, the big data headline was the incredible statistic that 90% of all data in the history of the entire human race had been created in the previous two years. The amount of structured and unstructured data we’ve created was so mind-boggling that we deemed it […]
So You Want to be a Big Data Analyst?
With the increasing use of big data by organizations in every field, the need for big data analysts will continue to grow. Big data analysts examine vast amounts of varied data. They uncover hidden patterns, customer preferences, and market trends. One of the primary differences between a big data analyst and a data scientist is […]
How AI Empowers Machine Learning to Be More Democratized
Click to learn more about co-author Adam Carrigan. Click to learn more about co-author Jorge Torres. Traditionally, machine learning tools were only available to enterprises with the necessary budget and expertise. Now, AI is empowering machine learning to be democratized to reach more users, allowing them to make the business intelligence-driven decisions that could transform […]
The Emergence of Open Analytics
Click to learn more about author Dipti Borkar. As businesses are increasingly becoming more data-driven and need to make faster, more informed decisions, the traditional data warehousing approach for accessing and analyzing data is becoming more impractical, time-consuming and likely to increase cost, effort, and vendor lock-in. It assumes data needs to be ingested and […]
BAE Systems Partners with UiPath to Expedite Machine Learning Adoption
A recent press release states, “BAE Systems is a technology partner with robotic process automation (RPA) leader, UiPath, in developing suites of software robots that its customers can use to automate high-volume, repetitive business processes. ‘RPAs fuel machine learning tools by feeding them high volumes of structured data necessary for it to begin learning and […]
Putting Structure Around Unstructured Data
Click to learn more about author Mark Cassetta. Structured data — things like credit card information and social security numbers — is easily tracked and analyzed. Unstructured data, on the other hand, is much more difficult to identify and use. This data includes information buried deep within documents users create and consume every day, including […]