What is Data Mining?
Data mining is the process of uncovering relationships and patterns in large datasets. This advanced form of data analysis draws from AI, statistics, and machine learning to help users locate important information. Those who are skilled at data mining can offer their organization insights about customer needs, as well as suggestions for how to cut down on costs and increase revenue.
The current demand for efficient and effective methods for data mining is prevalent across industries. Data mining is commonly used in fields like healthcare and pharmaceuticals, as well as careers that use geographic mining, such as spacecraft design, asteroid mining, and GPS-powered navigation tools like Google Maps. As more data is created, this need will likely continue to increase in the coming years. Analysts predict that the global market for data mining tools will increase from $552 million in 2018 to $1.31 billion by 2026.
Deciding which data mining tool is best for your needs often depends on professional goals, as well as the kind of data that needs to be analyzed. This article will explore two of the best tools in 2021 for data mining, Oracle and KNIME, to see which one comes out ahead for data mining.
What is Oracle?
Considered to be the international leader in database software, Oracle provides users with multiple data mining algorithms that can be used for classification, regressing, prediction, and anomaly detection. Oracle’s algorithms are well-suited for a variety of tasks, such as prediction, classification, feature selection, regression, and anomaly detection.
Oracle Data Miner is equipped with powerful data mining options that are situated within the Oracle database. It allows Data Analysts, Data Scientists, and Business Analysts to create and deploy descriptive and predictive applications, as well as to integrate intelligent capabilities into already-existing applications. Oracle Data Miner’s in-database algorithms can execute a plethora of mining endeavors, like clustering, classification, and regression. In addition, Oracle Data Mining is particularly well-suited for Data Analysts and Data Scientists who are working with large datasets.
Benefits & Drawbacks to Using Oracle for Data Mining
When working with Oracle, there are several perks as well as some drawbacks for users to be aware of:
Benefits
- Oracle has great graphical capabilities.
- It works well with multilevel models.
- Oracle provides a centralized platform for data science infrastructure, projects, and tools.
- Because it is browser-based, Oracle doesn’t require the installation of any additional software.
- Even those who come from non-technical backgrounds can use Oracle to make professional dashboards with advanced analytics.
Drawbacks
- Licensing is confusing for some users. Once the initial contract period is over, the price can increase substantially. This platform tends to be much more expensive than competitors’ products in the long run.
- Report formatting can pose problems for some users.
- Some users feel that issues with scalability and performance should be addressed so that Oracle can provide a more seamless platform experience.
What is KNIME?
KNIME is an open-source and free data science and machine learning platform that allows users to design independent services and applications via a drag and drop interface. Its pre-built components make it easy and fast to create models without the need to enter any code. KNIME has an intuitive user interface that’s perfect for a variety of modeling and production endeavors.
KNIME can convert different databases, spreadsheets, and flat files into one standard format. The data in this format can then be normalized, analyzed, and configured so that it can then be represented visually and the information being conveyed can be easily accessed and understood by multiple stakeholders. KNIME is considered to be one of the most all-around organized tools for integrating machine learning and data mining capabilities.
Benefits & Drawbacks to Using KNIME for Data Mining
There are several advantages, as well as a few drawbacks, to consider when using KNIME for data analytics and data mining.
Benefits
- KNIME integrates well with SQL databases.
- Its intuitive drag and drop node function allows users to automate a variety of database processes, such as joining, reading, and writing.
- KNIME is particularly helpful for repetitive tasks because it can automate the process, which drastically reduces the time users would need to spend manually completing these tasks.
- It can seamlessly connect with other BI tools for hands-free file sharing.
- Even those who have not been formally trained in coding can use KNIME.
- KNIME can connect to a variety of languages, such as Python, JS, and R.
- It is open-source and free.
- KNIME’s online community is supportive and helpful for fielding questions.
Drawbacks
- Although it is useful for beginners, KNIME tends to slow down when extensions are installed.
- In terms of customization, Python and R scripts are required to customize certain needs.
- Loops can be difficult to handle using KNIME.
- KNIME lacks proper visualization capabilities.
- Tools such as Tableau are quicker to set up than KNIME.
- For users from non-technical backgrounds, KNIME can be difficult to use.
The Bottom Line
When comparing Oracle to KNIME, there are several important differences to consider. In terms of price, KNIME is free and open-source, whereas Oracle is considered to be a more expensive option relative to other data mining platforms. Oracle comes out ahead for graphical capabilities, but KNIME has an intuitive drag-and-drop node function that makes automation of processes a relatively easy task. For users who are not technically trained, Oracle is thought to be an easier platform to work with than KNIME for creating professional-looking dashboards.
The 2021 Gartner Report comparing KNIME and Oracle noted that KNIME’s overall rating of 4.6 was slightly above Oracle’s 4.2. In addition, 93% of KNIME users would recommend this platform to others, whereas only 71% would recommend Oracle. Therefore, in terms of overall user satisfaction, KNIME comes out slightly ahead of Oracle.
Ultimately, when deciding which data mining tool or tools may be right for your organization, cost, capabilities, usability, and compatibility are all important factors to consider, but many good options like Oracle and KNIME are available.
Hands-On Data Analytics & Data Science Classes
For those who want to learn more about data mining, Noble Desktop’s data science classes provide a great option. Courses are available in-person in New York City, as well as in the live online format in topics like Python and machine learning. Noble also has data analytics courses available for those with no prior programming experience. These hands-on classes are taught by top Data Analysts and focus on topics like Excel, SQL, Python, and data analytics.
In addition, more than 100 live online data analytics courses are also available from top providers. Topics offered include FinTech, Excel for Business, and Tableau. Courses range from three hours to six months and cost from $219 to $27,500.
Those who are committed to learning in an intensive educational environment can enroll in a data science bootcamp. These rigorous courses are taught by industry experts and provide timely, small-class instruction. Over 40 bootcamp options are available for beginners, intermediate, and advanced students looking to learn more about data mining, data science, SQL, or FinTech.
For those searching for a data science class nearby, Noble’s Data Science Classes Near Me tool makes it easy to locate and learn more about the nearly 100 courses currently offered in the in-person and live online formats. Class lengths vary from 18-hours to 72-weeks and cost $915-$27,500. This tool allows users to find and compare classes to decide which one is the best fit for their learning needs.