Companies understand that data mining can provide insights to improve the organization. Yet, many struggle with the right types of data to collect, where to start, or what project may benefit from data mining.
Examining the data mining success of others in a variety of circumstances illuminates how certain methods and software in the market can assist companies. See below how five organizations benefited from data mining in different industries: cybersecurity, finance, health care, logistics, and media.
See more: What is Data Mining? Types & Examples
1. Cerner Corporation
Over 14,000 hospitals, physician’s offices, and other medical facilities use Cerner Corporation’s software solutions.
Cerner’s access allows them to combine patient medical records and medical device data to create an integrated medical database and improve health care.
Using Cloudera’s data mining allows different devices to feed into a common database and predict medical conditions.
“In our first attempts to build this common platform, we immediately ran into roadblocks,” says Ryan Brush, senior director and distinguished engineer at Cerner.
“Our clients are reporting that the new system has actually saved hundreds of lives by being able to predict if a patient is septic more effectively than they could before.”
Industry: Health care
Data mining provider: Cloudera
Outcomes:
- Collect data from unlimited and different sources
- Enhance operational and financial performance for health care facilities
- Improve patient diagnosis and save lives
Read the Cerner Corporation and Cloudera, Inc. case study.
2. DHL
DHL Temperature Management Solutions provides temperature controlled pharmaceutical logistics to ensure pharmaceutical and biological goods stay within required temperature ranges to retain potency.
Previously, DHL transferred data into spreadsheets that took a week to compile and would only contain a portion of the potential information.
Moving to DOMO’s data mining platform allows for real-time reporting of a broader set of data categories to improve insight.
“We’re able to pinpoint issues that we couldn’t see before. For example, a certain product, on a certain lane, at a certain station is experiencing an issue repeatedly,” says Dina Bunn, global head of central operations and IT for DHL Temperature Management Solutions.
Industry: Logistics
Data mining provider: DOMO
Outcomes:
- Real-time versus week-old logistics information
- More insight into sources of delays or problems at both a high and a detailed level
- More customer engagement
Read the DHL and DOMO case study.
See more: Current Trends & Future Scope of Data Mining
3. NasdaqÂ
The Nasdaq electronic stock exchange integrates Sisense’s data mining capabilities into their IR Insight software to help customers analyze huge data sets.
“Our customers rely on a range of content sets, including information that they license from others, as well as data that they input themselves,” says James Tickner, head of data analytics for Nasdaq Corporate Solutions.
“Being able to layer those together and attain a new level of value from content that they’ve been looking at for years but in another context.”
The combined application provides real-time analysis and clear reports easy for customers to understand and communicate internally.
Industry: Finance
Data mining provider: Sisense
Outcomes:
- Meets rigorous data security regulations
- Quickly processes huge data sets from a variety of sources
- Provides clients with new ways to visualize and interpret data to extract new value
Read or watch the Nasdaq and Sisense case study.
4. PBS
The Public Broadcasting System (PBS) of the U.S. manages an online website to service 353 PBS member stations and their viewers. Their 330 million sessions, 800 million page views, and 17.5 million episode plays generate enormous data that the PBS team struggled to analyze.
PBS worked with LunaMetrics to perform data mining on the Google Analytics 360 platform to speed up insights into PBS customers.
Dan Haggerty, director of digital analytics for PBS, says “that was the coolest thing about it. A machine took our data without prior assumptions and reaffirmed and strengthened ideas that subject matter experts already suspected about our audiences based on our contextual knowledge.”
Industry: Media
Data mining provider: Google Analytics and LunaMetrics
Outcomes:
- Identified seven key audience segments based on web behaviors
- Developed in-depth personas per segment through data mining
- Insights help direct future content and feature development
Read the PBS, LunaMetrics, and Google Analytics case study.
5. The Pegasus Group
Cyber attackers compromised and targeted the data mining system (DMS) of a major network client of The Pegasus Group and launched a distributed denial-of-service (DDoS) attack against 1,500 services.
Under extreme time pressure, The Pegasus Group needed to find a way to use data mining to analyze up to 35GB of data with no prior knowledge of the data contents.
“[I analyzed] the first three million lines and [used RapidMiner’s data mining to perform] a stratified sampling to see which ones [were] benign, which packets [were] really part of the network, and which packets were part of the attack,” says Rodrigo Fuentealba Cartes of The Pegasus Group.
“In just 15 minutes … I used this amazing simulator to see what kinds of parameters I could use to filter packets … and in another two hours, the attack was stopped.”
Industry: Cybersecurity
Data mining provider: RapidMinder
Outcomes:
- Uploaded and analyzed three million lines of dataÂ
- Recommended analysis models provided answers within 15 minutes
- Data analysis suggested solutions that stopped the attack within two hours
Watch The Pegasus Group and RapidMiner case study.
See more: Top Data Mining Tools
