Every business entrepreneur cherishes the data that they get from their business. Usually, business owners have to hire a data analytics company that will help them to manage their data.
The data processing goals of small companies, however, may be fulfilled using tools that are currently available in the market. In this article, you will come across the 7 best data analytics tools for perfecting data management. Also, we will explain how to use data analysis to increase positive customer experiences.
Data Analytics Process
Businesses are looking for fresh analytics and insights into their customers and prospects, financial performance metrics, and processes. Data analytics can help them make better decisions, leading to higher sales growth.
Whether you’re in charge of the organization’s dashboard or the glorified spreadsheet maintainer, your users want to look at their data and get answers. The data analytics process assures that you have captured and analyzed all the relevant information before you consider yourself done.
Need of Data Analytics
In every business, there are decisions and policies to be made based on information that is currently available. Organizations are curious about various aspects of their businesses and need valuable information that can help them develop relevant policies.
Most of the organization’s data get stored offline and in paper format; hence, it is not easily accessible. By taking assistance from Business Intelligence (BI) software, both internal data and external data can be used efficiently.
Data analytics is a computer-assisted method. The process involves data extraction, data cleaning, statistical analysis, visualization, and presentation. Therefore, data analytics is an important technique for the business intelligence of every company.
List of 7 Best Data Analytics Tools
Now, it’s time for you to check out the most valuable and trusted data analytics tools available in the market.
It is a free data analytics tool that lets you make quick and easy visualizations of your data. You can upload any spreadsheet, extract insights and publish them in a few minutes, thanks to the automatic chart recognition.
Whatagraph provides a fast and simple way to share insights from spreadsheets and databases by embedding interactive graphs, maps, charts, and more straight into your web app.
Tableau is changing the way users interact with data. The software helps users explore and visualize data in ways that were not possible before. Whether it’s a simple bar chart or a sophisticated predictive system, Tableau recognizes it can do whatever you want.
That’s because it’s designed for the way you think about data, and not just the way databases work. Whether it’s for dashboards, customer retention analytics, or comparing sales trends by region, Tableau can accommodate almost any need when it comes to using data.
RapidMiner is an open-source data analytics software package. It makes complex analytical tasks easy for business analysts and even non-programmers through its graphical user interface without any need for programming skills.
It enables the processing and visualization of large amounts of data, delivering value to organizations that are increasingly dealing with very large amounts of data. RapidMiner is an analytics tool that supports all enterprise businesses in their decision-making. Moreover, it is a data science platform that is quite popular among companies of all sizes.
RapidMiner can offer peak performance in any industry because right from modeling to deployment, it is present at every single stage.
4. Apache Spark
Apache Spark provides general execution graphs to perform in-memory computing that can handle both iterative algorithms and interactive queries, which is similar to the MapReduce model of computation. The Apache Spark project is an open-source, unified framework for processing huge amounts of data.
Spark has many benefits for users in its ability to reduce required maintenance, create better security, and accelerate development. Many users find that Apache Spark increases performance and reduces their need to do tedious work manually.
QlikView is a data visualization tool used for reporting, analyzing, and exploring data. It has easy-to-use navigation features making the building of reports a breeze. It makes use of fast-loading visuals that are easy to manipulate.
The QlikView analytics platform combines data exploration, visual analysis, and mobile data preparation with an open information architecture that was purpose-built for self-service analytics.
KNIME is a visual dataflow programming and analytics platform that gives people who work with data the power to do anything they can imagine with data. It supports beginners with its visual workflow editor and experienced users through the programming API (client) as well as the Python API, the R API, and the REST API.
You’re not limited to using predefined nodes either – you can combine existing nodes to create new workflow elements or extend KNIME with your own code in Java. This will dramatically reduce development time allowing you to spend more time focusing on the results of your data analytics rather than trying to get there in the first place.
It can help you monitor in real-time what matters most—systems, applications, and business processes—to take action and make decisions with confidence and speed.
Splunk Enterprise is the platform for operational intelligence, real-time monitoring, analytics. Also, it offers search-based security to more than 10,000 enterprises worldwide.
You might be aware of the fact that how a business manages data is ultimately going to determine its fate. For this reason, managers today are investing heavily in tools and technologies that can help them analyze the business effectively and efficiently. We hope that this post helps you in choosing the best data analytics tools to speed up the growth of your business.
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