Big Data Analytics

Start with the key terms

The key terms flashcards introduce structured, unstructured and semi-structured data alongside data analytics, data integrity and extract, transform, and load. They also include numerical and categorical data. University students can use the deck to become familiar with the vocabulary before moving to the maps. Teachers can use it to identify terms to discuss with students.

Explore the mind maps

Big Data Analytics brings together unstructured data, the primary goal of analytics, and technologies including NoSQL, Hadoop and MapReduce. Use it to see how these terms are grouped in a single resource.

Big Data & Analytics offers another view, with characteristics such as volume, variety and velocity, as well as analytics techniques and challenges. The Data Mining from Big Data 4V-s map also covers data characteristics, including volume, velocity, variety and value. Compare the maps to see which terms appear in each.

Use a quiz alongside a map

The quiz on big data analysis and technology concepts includes text analytics questions about parsing text and using extracted information for a context-specific search. After studying the key terms and a map, try that quiz. Then return to the maps or flashcards to review relevant terms.

The quiz and maps cover different aspects of the topic, so they are useful as complementary resources rather than matching question for question. The Data Science map adds a view of skills, including programming, mathematics and working with unstructured data.

Place the topic in its unit

Big Data Analytics is a section of the Big Data, Hadoop and Spark unit in Databases and data science. The maps on this page include Hadoop and MapReduce, giving you terms to carry into the wider unit. Pick a map and use it to organize your study before trying a quiz.