It may take time and effort to extract and transform data into something usable. However, when it has finished, data analytics can offer you greater insights for the sake of your business, customers, and industry. There are three categories of data analytics which offer diverse insight levels.
They include traditional business intelligence (BI), embedded analytics, and self-service analytics. If you are not taking advantage of any data analytics tools, you are recommended to do so. You may be able to do your work with tools, but they will help you to make it easier.
BI and self-service analytics users can generate more analysis than data scientists. Thus, regardless of the level of your insight, it would be a great option to use tools for data analytics. If you don’t know which tool to choose, this following information will help you to find some ideas.
When we are talking about a tool for data analytics, Tableau is something that shouldn’t be missed. This tool is capable to help you make graphs, charts, dashboards, maps, and applications. More interestingly, this tool also lets you publish and share your creations. It can be used on some different platforms including macOS and Windows.
As one of the best data analytics tools, Tableau not only offers solutions for server and desktop but also provides an online solution as well. You can get into Tableau Online to connect with any dataset. Since it is online, you can connect to your data anytime and anywhere you want.
Tableau has six products for data analytics including Tableau Server, Tableau Online, Tableau Desktop, Tableau Public, Tableau Reader, and Tableau Prep. If you use the Tableau Public, you don’t need to pay any cost for it. However, Tableau Creator costs you around $70 each month. There are some other plans available too.
When it comes to features, Tableau has everything from an automatic phone to tablet layouts. This tool also makes it possible to customize these layouts. Moreover, this tool also allows you to create transparent filters, highlighters, and parameters. There is no doubt that Tableau is among the best data analytics tools available.
RapidMiner is a kind of software platform for machine learning, data preparation, deep learning, predictive model deployment, and text mining. This tool offers all data prep capabilities. The tool can help data scientists and analysts in increasing their efficiency through automatic machine learning. It highlights speed to insight for complicated data science.
Pre-built workflow, data connectivity, and machine learning elements are what included to its visual interface. With Python and R integration, this tool can automate the model selection, data prep, predictive modeling, as well as what-if gaming. It also speeds up the work by a combined collaboration and development environment.
As one of the best data analytics tools, RapidMiner doesn’t require you to write the code. It can help you with its RapidMiner Radoop. This tool is available for free with a 10,000 data rows plan. Some packages are available for the plan details. The Small plan costs $2,500 per year.
RapidMiner offers a variety of features including built-in security controls, visual workflow designer for Sparx and Hadoop, centralized workflow management, and team collaboration. Then, its Radoop allows you to employ large datasets for training in Hadoop. It also offers support for Hadoop impersonation and Kerberos.
KNIME is an open-source, class analytics platform created with the data scientist in mind. KNIME’s visual interface involves nodes for everything from digging out the data to presenting it. Here, it emphasizes statistical models. This one of the best data analytics tools enables you to develop machine learning models.
This analytics platform incorporates a few other tools such as H2O, Hadoop, R, Python, and other structured and unstructured data types. It also supports leading edge, data science applications like medical claim outline detection, social media sentiment analysis, text mining, and market basket analysis.
There are a lot of features available in KNIME. It features a GUI that uses the drag-and-drop facility to create visual workflows. Then, coding skills are not required to use this tool. It enables you to use the tools along with diverse domains like scripting in Phyton and R.
Furthermore, it also features multi-threaded data processing, in-memory processing, as well as guidance for building workflows. It even enables you to personalize charts. As one of the most popular data analytics tools, KNIME is something that you can count on, especially because it is easy to learn.
This is open-source data analytics software you can find out there. Even if you have messy data, this tool can help you clean, extend, as well as transform it. This tool enables you to transform data from one platform to another. It can be helpful to extend data employing external sources and web services.
OpenRefine also comes with a variety of features. You can work with a large set of data effortlessly. For some services, you are allowed to upload the data to the central database too. It also enables you to import JSON, RDF, TSV, CSV, XML, Google Fusion Tables, and Google Spreadsheets.
This is one of the free data analytics tools out there. Yet, you can count on this tool to help you deal with your data properly. It supports a lot of file formats as well. It is a desktop application which can be employed by small, medium, and big companies.
In conclusion, data analytics tool are not created equal. Each of them offers different features and characteristics. Depending on your needs, you can choose the one that suits you the most. Don’t forget to consider the available features offered. Hope you enjoy this list of data analytics tools!