The Data Mining Market

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The data mining market includes the practices and services of analyzing large data sets to extract new insights and information.

As making data-backed decisions becomes more important for companies, the demand for a continuous stream of data to analyze is growing.

See below to learn all about the data mining market:

The Market for Data Mining
Data Mining Features
Benefits of Data Mining
Data Mining Use Cases
Data Mining Providers

The Market for Data Mining

The data mining market that consists of mining tools and services was valued at $591.2 million in 2018. It’s expected to grow to $1.03 billion by 2023 due to a compound annual growth rate (CAGR) of 11.9%.

The global data mining market isn’t spread out equally over the world:

The U.S. is expected to maintain a 12.8% growth momentum.
Germany is estimated to add over $27.4 million to the market in the next five to six years.
Eastern Europe will introduce over $32.5 million worth of data mining projects.
Japan’s local data mining market is approximately $59.8 million.
China is expected to add $121.2 million in data mining projects over the next few years.

Industry-wise, data mining is used most by companies that are user and customer-reliant in sectors such as communications, retail, health care, media, advertising, education, and finance.

Data Mining Features

To make the most out of data mining, the practice is done in five primary steps:

Data sourcing
Selecting the work environment
Data segmentation and categorization
Mining for insights
Translating and visualizing the results

Depending on the type of insights and information you’re looking to generate, data mining is split into two categories: predictive data mining and descriptive data mining.

Predictive data mining analysis types:

Classification analysis
Regression analysis
Time series analysis
Prediction analysis

Descriptive data mining analysis types:

Clustering analysis
Summarization analysis
Association rules analysis
Sequence discovery analysis

Benefits of Data Mining

Data mining allows analysts to generate insights and information from data about their target client base.

Whether it’s predictive or descriptive data mining, it can help understand companies where they stand in the market and what their next steps should be.

Other data mining benefits include:

Enables business to make informed decisions
A source for reliable information
Discovery of underlying patterns to improve quality and efficiency
Build risk models for fraud and cyber attacks
Shift into automation
Discover time-sensitive variants for sales and marketing
Identifying the most profitable client and customer types
Identifying and retaining the most valuable employees and business partners

Data mining benefits tend to vary depending on the industry, as companies with more direct access to user and activity data are able to generate more accurate and applicable insights.

“Data mining has a wealth of applications,” says Dave Johnson, a technology journalist in his article with Business Insider.

“It’s commonly used to acquire customers, increase revenue, improve cross-selling and upselling, increase customer loyalty, detect fraud, and improve operational performance and efficiency.”

Data Mining Use Cases

Ever since data mining was first introduced in the 1990s, thousands of companies in various industries were able to use it to better understand their audiences and work operations and figure out how to improve them.

Tubi

Tubi is an American content platform and streaming service owned by Fox Corporation. Founded in 2014 and based in San Francisco, California, Tubi has over 30 million active monthly users.

Standing against media giants like Netflix and Hulu that make their own content, Tubi needed to be creative and smart with attracting its audience.

With Sisense’s help, everyone at Tubi would learn SQL and learn how to use the data tables within Sisense for Cloud Data Teams.

“Sisense for Cloud Data Teams allows us to go into the data, manipulate it, structure it very quickly, and then display it out to our team within a matter of minutes,” says Rameen Mahdavi, a data scientist at Tubi.

“We could still communicate data with combinations of other tools, but it wouldn’t be as quick to deliver results as it is with Sisense for Cloud Data Teams.”

SustainHub

SustainHub is a project that aims to provide a systematic and efficient approach for compliance and sustainability data for products and manufacturing. Based in Stuttgart, Germany, SustainHub consists of 15 partners from seven countries.

It’s challenging for European manufacturers to consistently get information from suppliers regarding the materials used in products. Using RapidMiner, SustainHub is able to help manufacturers set a joined online platform to share up-to-date data.

“Using RapidMiner’s data mining functionality, we can do risk analysis, checking for errors or omissions, flagging certain substances or products, and searching for alternatives,” says Simon Fischer, SVP of engineering at RapidMiner.