The benefits data analysis has brought to our everyday endeavour cannot be overemphasized. It has helped in enhancing productivity, making informed decisions and avoiding dangerous pitfalls. A good data analysis has proven beyond measure to be a virtual advisor and guide for businesses, industry experts and policymakers. Below are the best tools suitable for descriptive, diagnostic, prescriptive and predictive types of data analysis.
Microsoft Power BI
Microsoft Power BI is an excellent tool for data aggregation, analysis, visualization and sharing. Its benefits include chart creation and data modeling which can be useful for performance measurement within an organization. Its modus operandi is to connect disparate data sets. In usage, a good understanding of EXCEL may greatly discountenance the need for rigorous training in Microsoft BI.
Used mostly within organizations, it can access image recognition and text analytics; create and integrate machine learning models. When other data sources are to be harnessed, it serves as a good hybrid support. Its components like the power query, power view, power pivot help in data sharing and creation. Power BI Desktop, Power BI Pro and Power BI Premium are the three levels available for power BI. It is compatible with Windows, Mac, Linux, Android, iOS.
Tableau
This tool is noted more for data extractions and connections and optimally great for analysis. Its use by data engineers and analysts stems from its ability to process big data. While in use, its optimization quality enhances progress. The knowledge of coding is not a prerequisite for the use of Tableau, which makes it less esoteric. Although its functions are more suitable for big data, it still helps to secure data without scripting because its security features are inbuilt.
The different versions that Tableau comes with include Tableau Server, Tableau Cloud, Tableau Desktop. Tableau can integrate with over 250 applications. Tableau Desktop can allow coding and customization. In the case of Tableau Server, its work entails sharing workbooks, visualizations created in Tableau Desktop application. It is also compatible with Window, Web-based Mac, Linux, Andriod, iOS.
RapidMiner
Apart from being a pioneer analytics package that offers analytics capabilities and versatility, its predictive, data and text mining qualities make it desirable to use. This tool helps business analysts make enterprising decisions with its easy-to-use interface which does not require a degree in data science. It has a unique statistical pattern to text analysis. It also allows for easy classification and analysis of unstructured data sources because it is a memory based system.
On a broad scale, it is good for research, rapid prototyping and application development. It also supports machine learning process. It is an open source. RapidMiner functions extend to RapidMiner Marketplace; which is capable of creating data and algorithms.
Orange
Orange’s performance of simple data analysis with data visualization and exploration of statistical distributions are the reasons it enjoys wide usage. Added to its open source advantage, its tasks cover predictive modeling, algorithm evaluation and preprocessing. At advance level of understanding Orange, it can be used to manipulate data. Its add-on externalities include natural language processing, network analysis. Molecular biologists find Orange extremely useful in ranking genes through enrichment analysis and differential expression.
It is known to have a user-friendly interface which can explore data for qualitative analysis. Prototyping of data analysis is extremely fast because of its graphic user interface that helps on exploratory data. It is compatible with MAC, WINDOWS AND LINUX operating systems. It also allows installation from Python Package index repository.
Konstanz Information Miner (KNIME)
KNIME has been tagged to be arguably the most comprehensive tool, especially for statistics and drag-and-drop analytics. It does not have a locked feature and supports easy movement of data between environments. It is also suited for natural language processing and API integration. It’s an open source and quite easy to learn. It works well with Microsoft Azure and AWS. Blending tools from different domains and Multi-threaded data processing are possible on its platform. KNIME integrations can help in the import, export and access of data from big data platforms. It can also integrate scripting and machine learning.
Platform extension is possible on the KNIME platform; its server can support collaborations and automate the execution of workflow.
OpenRefine
It is strong tool for data clean up and data transformation into different formats. OpenRefine is a Java program that does not run on the cloud but on your machine. It does not require an internet connection. Although it has the capability of extending data with web services and external data, it also ensures safety and privacy of data unless intentionally shared. Its modus operandi is to use your web browser to interact with a small server it runs on your computer. It is known to be a good easy explorer and exporter of data in Microsoft Excel, TSV, CSV, HTML table. Google Fusion tables and Google spreadsheets can be imported from OpenRefine.
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