Industry Data: Best Industry Datasets & Databases

Industry Data Explained

How is Industry Data collected?

The type of industry data being collected usually determines the source or method of collection. Considering there are usually hundreds of industries in any given economy, the methods may vary, but there are some common sources and means of collection of industry data. Industry data can be collected from reports on research conducted in markets. Industry data can also be found in articles and journals. Another source of collection are industry classification systems, as well as industry forecasts, government reports, statistics, industry associations, brands, competitors and global organization reports. All of these sources contain data determined by research and observations of specific industries.

What are the attributes of Industry Data?

Since industry data is intelligence on a given industry, then an industry dataset should typically contain information on the characteristics of that industry. These include features or characteristics such as sectors in the industry, which detail the extent of creation in the industry. Industry data can also tell a user about the amount of resources required for participation in the industry, labor, financials, barriers to entry in the industry, level and type of competition in the industry, structure of the industry, including competition and monopolies. Attributes of a typical industry dataset also include details on competitive advantages, the life cycle of the industry from nascent to decline, and the negative by-products the industry’s activities may produce, such as pollution. Furthermore, details on a typical business model for that industry, as well as what type of labor it requires, are important industry data attributes.

What is Industry Data used for?

In a nutshell, if you are seeking information on an industry, its components, and how it performs, then industry data is what you need. Industry data is also useful in the use case of machine learning. Machine learning is the process of increasing the strength and accuracy at which an algorithm operates. This determines its response to data inputs, and so industry data is essential for improving the capacity or capabilities at which the algorithm can analyse data and make informed and accurate decisions. It is used in feasibility reports and expansion strategies.

How can a user assess the quality of Industry Data?

There are a lot of features, components and characteristics that make up an industry dataset. It’s important that an industry dataset is of high quality. For industry data to pass data quality assessment, it needs to be consistent and up to date. It must be timely, and it should also contain the necessary attributes of the particular industry it is providing information about. To further assess the quality of industry data, you need to verify that the data provider is reliable. You can do this by checking previous buyer reviews to get an idea of what exactly other clients thought about the data provider and its services.