10 Data Analytics Tools Recommended for Your Business
Data Analytics plays a vital role in shaping up the business model of an enterprise. It utilizes several data collection methods like surveys, interviews, and statistical tools to analyze the data and represent them with graphs, charts, and tables. These tools provide a comprehensive solution for data analysis.
Why Do You Need Data Analytics Tools?
Each year, organizations produce a vast amount of raw data. It comes from various sources like Financials, Sales, Marketing, Customers, in-house operations. This raw data contains much valuable information that could increase a company’s overall performance. Data Analytics tools collect data, processes it into a significant resource and deliver solutions based on our queries. Hence, few advantages of using Data Analytics tools are:
• With Data Analytics Tools, we can create monthly or yearly progress reports. This feature is crucial that can keep companies on the right track.
• These tools can graphically represent survey samples of product performance.
• Data Analysis Tools like Google Analytics produce real-time reports.
• You can get important information such as demographic details, shopping behaviour, the popularity of a product, customers’ feedback from the tools.
POPULAR DATA ANALYTICS TOOLS
Another product from Google is Google sheet. It is a cloud-based spreadsheet that provides essential database management and data analytics features. It helps to imagine, process and correspond the data. With Google Add On element, Google sheet can integrate third-party services. A user can integrate Google Sheet with Google Analytics and generate customized reports accordingly. This feature lets you analyze your sales and marketing data, manage your inventory, understand customer behaviour and much more. Google sheets have many premium plans for businesses.
Python is a high-level (general purpose) programming language. Different fields like Web-development, Machine learning, Business Applications, CAD Applications, Data Science, and Data Visualization uses this software. Python focus on readability. It has a large developer community, unlike C language. This extensive library makes the programmer’s job easier to extract data from the internet, handle cumbersome computational tasks on massive data, and represent information in graphical form.
Power BI is a cloud-based multi-purpose software and a business intelligence tool. It assists companies to gather, inspect and visualize data from other departments. Power BI provides immense insight to companies about their operations and performance. The software permits to make of more correct decisions based on factual data. It also helps to create compelling charts and graphs. Power BI works equally on Windows and IOS platforms.
SAS (known as Statistical Analysis System) is a software suite developed by SAS institute. It handles features like data management, business intelligence, predictive analysis, advanced analytics and much more. It is available only on Windows. This statistical software extensively used in universities and technical industries.
Free Data Analytics Tools
Knime is also known as Konstanz Information Miner. It is free software and provides an open-source platform with data analytics, reporting and integration facilities. Knime can integrate several attributes of data mining and machine learning by its data pipeline model. It permits users to build data pipelines (flows) visually, help execute analysis steps, and examine the models and results and utilize interactive views and widgets. Knime is java-based. Users can add plugins to improve functionality.
Qlikview saves a lot of time and helps in making effective business decisions. It helps to understand the data in details and gain insights. It provides users to explore and find data that are difficult to locate by query tools. Qlik is easy to use, especially for those users who have little knowledge of programming. It uses memory manipulations to manipulate data sets. It has robust data visualization capacity. It is scalable to a high degree and offers an immediate response.
Tableau is an analytics platform that visualizes the data, provides insight to the user to solve organizational problems. It helps to churn out most of the data. Tableau can handle sales data analysis, user density monitoring, segmentation of consumers, Tracking the budget expense, categorizing the data.
Recommended Data Analytics Tools
R is a programming language. This free and open-source software works in the data science field and helps make statistical models and visualize projects. The Sisense data develops statistical models that automatically updates new information flows into the model.
Apache Spark provides an open-source processing system. It works on a data processing framework. Apache Spark can give solution to a wide range of data issues. It is a user-friendly platform that can easily handle batch processing, machine learning and large scale SQL.
Data Analytics tools provide a comprehensive platform to boost the overall performance of businesses. These tools extract raw data and process it into information that can handle a company’s queries. These tools can generate performance or survey-based reports in the form of graphs, pie charts, and tables. Data Analytics provides greater insight and predicts the future performance of a company. Hence, we have chosen some of the best popular tools in the market. And they are Google Analytics, Google Sheets, Power BI, Python programming, R Programming, SAS, Knime, QlikView, Tableau, and Apache Spark. These tools manage the database and help to generate accurate reports as per the queries. Most of them are cloud-based, and installation is easy.