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Most Popular Analytics Software

Do you want to learn about business analytics software? Or you need to learn about popular business analytics software? I think these must be some of the questions that pop up in your mind. These are so interesting questions, and they are not so hard or weird to answer. You see, there are many popular business analytics software out there in the world. They are all waiting for a person like you to come and get them and use them.

Analytics software is the thing to have so you can analyse your business data more easily. With one such tool, you would be able to backup and restore all your data. This would help you out a lot, especially if you have them stored at a remote location, or in a different country. And do you know where are currently most popular analytics software? In this article, I am going to tell you about them.


R is now one of the most popular analytics tools in the industry. It has surpassed SAS in usage and is now the Data analytics tool of choice, even for companies that can easily afford SAS. Over the years, R has become a lot more robust. It handles large data sets much better than it used to, say even a decade earlier. It has also become a lot more versatile.

1800 new packages were introduced in R between April 2015 and April 2016. The total number of R packages is now over 8000. There are some concerns about the sheer number of packages, but this has certainly added a lot to R’s capabilities. R also integrates very well with many Big Data platforms, which have contributed to its success.


Python has been one of the favorite languages of programmers since its inception. The main reason for its fame is the fact that it’s an easy-to-learn language that is also quite fast. However, it developed into one of the powerful Data analytics tools with the development of analytical and statistical libraries like NumPy, SciPy etc. Today, it offers comprehensive coverage of statistical and mathematical functions.

Increasingly, we are seeing programmers and other tech folks moving into analytics. Most of these guys are already familiar with Python, and therefore, it has become a Data analytics tool of choice for many data scientists.


One of the best BI tools for data analysts: datapine


Visual drag-and-drop interface to build SQL queries automatically, with the option to switch to, advanced (manual) SQL mode

Powerful predictive analytics features, interactive charts and dashboards, and automated reporting

AI-powered alarms that are triggered as soon as an anomaly occurs or a goal is met

datapine is a popular business intelligence software, that is focused on delivering simple, yet powerful analysis features into the hands of beginners and advanced users that need a fast and reliable online data analysis solution for all analysis stages. An intuitive user interface will enable you to simply drag-and-drop your desired values into datapine’s Analyzer and create numerous charts and graphs that can be united into an interactive dashboard. If you’re an experienced analyst, you might want to consider the SQL mode where you can build your own queries or run existing codes or scripts. Another crucial feature is the predictive analytics forecast engine that can analyze data from multiple sources which can be previously integrated with their various data connectors. While there are numerous predictive tools out there, datapine provides simplicity and speed at its finest. By simply defining the input and output of the forecast based on specified data points and desired model quality, a complete chart will unfold together with predictions.

We should also mention robust artificial intelligence that is becoming an invaluable assistant in today’s analysis processes. Neural networks, pattern recognition, and threshold alerts will alarm you as soon as a business anomaly occurs or a previously set goal is met so you don’t have to manually analyze large volumes of data – the data analytics software does it for you. Access your data from any device with an internet connection, and share your findings easily and securely via dashboards or customized reports for anyone that needs quick answers to any type of business question.


One of the most useful general-purpose programming languages for data analysts: Python


An open-source solution that has simple coding processes and syntax so it’s fairly easy to learn

Integration with other languages such as C/C++, Java, PHP, C#, etc.

Advanced analysis processes through machine learning and text mining

Python is extremely accessible to code in comparison to other popular languages such as Java, and its syntax is relatively easy to learn making this tool popular among users that look for an open-source solution and simple coding processes. In data analysis, Python is used for data crawling, cleaning, modeling, and constructing analysis algorithms based on business scenarios. One of the best features is actually its user-friendliness: programmers don’t need to remember the architecture of the system nor handle the memory – Python is considered a high-level language that is not subject to the computer’s local processor.

Another noticeable feature of Python is its portability. Users can simply run the code on several operating systems without making any changes to it so it’s not necessary to write completely new code. This makes Python a highly portable language since programmers can run it both on Windows and macOS. An extensive number of modules, packages and libraries make Python a respected and usable language across industries with companies such as Spotify, Netflix, Dropbox and Reddit as the most popular ones that use this language in their operations. With features such as text mining and machine learning, Python is becoming a respected authority for advanced analysis processes.

MySQL Workbench

SQL consoles example: Mysql Workbench


A unified visual tool for data modeling, SQL development, administration, backup, etc.

Instant access to database schema and objects via the Object Browser

SQL Editor that offers color syntax highlighting, reuse of SQL snippets, and execution history

MySQL Workbench is used by analysts to visually design, model, and manage databases, optimize SQL queries, administer MySQL environments, and utilize a suite of tools to improve the performance of MySQL applications. It will allow you to perform tasks such as creating and viewing databases and objects (triggers or stored procedures, e.g.), configuring servers, and much more. You can easily perform backup and recovery as well as inspect audit data. MySQL Workbench will also help in database migration and is a complete solution for analysts working in relational database management and companies that need to keep their databases clean and effective.


predictive analytics software: SAS Forecasting


Automatic forecasting for a large number of entities or products, including hierarchical forecasting

Scalability and modeling by combining 2 or more models and creating an ensemble

An unlimited model repository that includes time series and casual methods such as ARIMA and ARIMAX

SAS Forecasting for Desktop has established itself as one of the most prominent advanced data analysis software that offers a wide range of forecasting methods, including hierarchical reconciliation, event modeling, what-if analysis, and scenario planning. Their features comprise 7 core areas of forecasting processes, some of them we already mentioned: automatic forecasting, scalability and modeling, unlimited model repository, easy-to-use GUI, event-modeling console, what-if analysis, and data preparation. Based on the variables that you enter in the modeling process, SAS will automatically select variables to generate forecasts to unravel what happens in your business.

Moreover, with a bundle of the SAS Forecast Server, and Visual Forecasting solutions, this data software enables users to produce a large number of forecasts, and automate their processes. Since the company is on the market for decades, they have established themselves as an authority figure in predictive analytics, and it certainly makes sense to give them a try.

erwin data modeler (DM)

data analyst tools example: erwin data modeler


Automated data model generation to increase productivity in analytical processes

Single interface no matter the location or the type of the data

7 different versions of the solution you can choose from and adjust based on your business needs

erwin DM works both with structured and unstructured data in a data warehouse and in the cloud. It’s used to “find, visualize, design, deploy and standardize high-quality enterprise data assets,” as stated on their official website. erwin can help you reduce complexities and understand data sources to meet your business goals and needs. They also offer automated processes where you can automatically generate models and designs to reduce errors and increase productivity. This is one of the tools for analysts that focus on the architecture of the data and enable you to create logical, conceptual, and physical data models.

Additional features such as a single interface for any data you might possess, no matter if it’s structured or unstructured, in a data warehouse or the cloud makes this solution highly adjustable for your analytical needs. With 7 versions of the erwin data modeler, their solution is highly adjustable for companies and analysts that need various data modeling features.


One of the best ETL tools: Talend


Collecting and transforming data through data preparation, integration, cloud pipeline designer

Data governance feature to build a data hub and resolve any issues in data quality

Sharing data through comprehensive deliveries via APIs

Talend is a data integration platform used by experts across the globe for data management processes, cloud storage, enterprise application integration, and data quality. It’s a Java-based ETL tool that is used by analysts in order to easily process millions of data records, and offers comprehensive solutions for any data project you might have. Talend’s features include (big) data integration, data preparation, cloud pipeline designer, and stitch data loader to cover multiple data management requirements of an organization. This is an analyst software extremely important if you need to work on ETL processes in your analytical department.

Apart from collecting and transforming data, Talend also offers a data governance solution to build a data hub and deliver it through self-service access through a unified cloud platform. You can utilize their data catalog, inventory and produce clean data through their data quality feature. Sharing is also part of their data portfolio; Talend’s data fabric solution will enable you to deliver your information to every stakeholder through a comprehensive API delivery platform. If you need a data analyst tool to cover ETL processes, Talend might be worth considering.


It is hard to determine which business analytics software that is the best among all the products. Our specialists did their homework and presented you with top-rated products. These are most popular analytics software programs worth checking out.

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