Best Data Analysis Tools and Software in 2022

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The term “data” has been around for a very long time. Data is essential for decision-making in today’s world when 2.5 quintillion bytes of data are produced every day. However, how do you believe we can manage that much data? The function of a data analyst is one of several important roles in the industry today that work with data to obtain insights. To extract insights from data, a data analyst has to use various techniques. The top tools that every aspiring data analyst to an experienced professional should have will be covered in this article on the Top 10 Data Analytics Tools.

The term “data analytics” describes the methods used to analyse data in order to increase productivity and financial benefit. In order to examine different behavioural patterns, data is taken from a variety of sources, cleaned up, and classified.

What is Data Analytics Tool?

Data analysts utilise software and programs known as data analytics tools to create and carry out analytical procedures that assist businesses in making better, more informed business choices while lowering costs and raising profits.

Key Features of Data Analysis Tools:

There is few features which you should keep in your mind before choosing any data analysis tools.

Raw Data Processing:

The act of processing data refers to gather and intelligently arrange data. Data modelling involves taking complicated data sets and visualising them as diagrams, charts, or schemas. Here, data must be comprehensible and interpretable to be used in decision-making. Data must be able to be gathered from many sources and in various formats using tools. The following characteristics are necessary for data processing tools:

Data security:

The organization’s database and database management system are frequently connected with data analysis tools (DBMS). This implies that without adequate security, employees at any level may have access to confidential client information and corporate data. A smart data analytics platform establishes safeguards, permissions, and access level restrictions that prevent data breaches. Nevertheless, the capacity of users to interact with the given data should not be hampered by data security.

Data Integration:

Before choosing any analytical tool, data integration must be a crucial component. Information from databases and other storage types may be dispersed throughout an organization’s many locations. Such data should be easily importable and integrable with a decent tool. Connecting analytical tools to data sources should take only a brief time for data scientists.

Data Visualisation:

Most data analysis methods end with data visualisation. The ability to discuss and convey findings with team members and executives is a requirement for data scientists and data analysts. Data visualisation techniques, such as graphs and charts, that make it simple to analyse and communicate data must thus be included in data analysis tools.

How to decide on Data Analysis Tools:

Once the data is prepared, you may experiment with various tools for analysis. How can you locate one that is ideal for your business? Learn who will be utilising your analytics solution and start by considering your firm’s business demands. Will it be utilised by data scientists and skilled analysts, by non-technical consumers who require an easy interface, or should it be appropriate for both types of users?

Some platforms provide an interactive experience for iterating on code development — typically using SQL — while others focus more on point-and-click analysis for less technical users. The tool should also provide support for visualisations relevant to your enterprise.

Think about a tool’s capacity for data modelling. Some people can support a semantic layer or do their own data modelling. If you wish to use one that doesn’t, you’ll need to model your data before analysis using SQL or a programme like dbt.

Finally, think about licencing and price. While some services are free, others require a licence or a subscription. Users should pay attention to the many reliable free solutions readily available because the most costly tools are only sometimes the most feature-complete.

 

Top 10 Data Analysis Tools and software in 2022:

Here, we discuss the top 10 data analysis tools and software. Go through this article and select the worthy data analysis tools.

Microsoft Excel:

Microsoft Excel is a platform developed by Microsoft company that will help you get better insights into your data. Microsoft Excel, one of the most widely used tools for data analytics, offers users features like sharing workbooks, working on the most recent version for real-time collaboration, and uploading data directly from a photo to Excel, among others.

Products:

  • For Home
  • For Business
  • For Enterprises

Features:

  • Microsoft 365 offers inclusive protection for employee data and customer information.
  • Data security is provided on all aspects of the Business Premium membership.
  • Data from databases, Azure, and Power BI may all be integrated through a connection to that platform.
  • To better comprehend data, you may make charts and graphs in Excel. It’s also simple to share.
  • Excel is a user-friendly program with mobile, desktop, and web versions but does not have comprehensive dashboards.
  • Almost every common analytics workflow can be supported by Excel, which can be expanded using its built-in programming language, Visual Basic.

Pricing:

  • The monthly user fee for the Microsoft 365 Business Basic membership is $6.
  • Limited trial editions are free for one month. The trial is a part of the Microsoft 365 package.
  • Each of these goods has a variety of variants with features and price points that vary.

USP:

Microsoft Excel’s ability to directly integrate analogue data from an image to an entirely editable format makes it unique.

Pros:

  • Excel is useful for easy analysis.
  • User-friendly interface which is easily accessible.

Cons:

  • It is not appropriate for large data analysis
  • It has a limit of about 1 million rows and
  • Has poor collaboration and versioning capabilities.

 

Microsoft Power BI:

Microsoft Power BI is a data analytics tools that allows you to create sophisticated, dynamic data visualizations from a variety of sources. It also allows you to communicate critical business insights that lead to success. Together, the Power BI tools translate raw data into a legible, simple format.

Products:

  • Power BI Desktop
  • Power BI Pro
  • Power BI Premium
  • Power BI Mobile
  • Power BI Embedded
  • Power BI Report Server

Features:

  • Applying sensitive tags or using the Bring Your Own Key option are two ways that Power BI safeguards your data on several levels.
  • Excel, Microsoft Azure, databases, and other sources may all be used to integrate data into Power BI seamlessly.
  • Power BI provides the ability to generate and distribute interactive data visualisations globally.
  • Reports and dashboards are seen via the mobile app, which is accessible on iOS and Android.
  • Power BI has recently come up with solutions such as Azure + Power BI and Office 365 + Power BI to help users analyse the data, connect the data and protect the data across various Office platforms.

Pricing:

A few of them are free for a limited time before you purchase the licensed versions. Power BI Premium costs $27.5 per month for each user.

USP:

Power BI is a product of Microsoft and works well with the industry-leading data analysis tools Microsoft Excel. Additionally, it is extremely extensible.

Pros:

  • Mobile app
  • Offers a free trial
  • Easy to use, especially if you already know Excel

Cons:

  • Too much data can slow it down
  • Data limits may require you to upgrade plans

 

Qlik Sense:

Qlik Sense is a data analysis tool developed by Qlik, an international, U.S.-based software company. A self-service business intelligence and data analytics platform from Qlik enables both on-premises and cloud implementation. Both technical and nontechnical people may easily explore and find data with the tool. Users using Qlik may alter a wide variety of charts using drag-and-drop and integrated SQL modules.

Product:

  • Data Integration
  • Data Analytics
  • Developer platforms

Features:

  • The role-based security model, report-level access control, multi-factor authentication, etc. are just a few of the security features that Qlik Sense boasts about.
  • Qlik Sense offers complete support for blending data from databases, files, cloud services, and business applications.
  • Qlik’s data visualisation is intelligent and automated; it changes dependent on the current situation.
  • Qlik Sense offers a robust, dynamic dashboard that makes it easy to spot crucial information.
  • it aims to accelerate business value through data by providing features such as Data Integration, Data Literacy, and Data Analytics.

Pricing:

  • Qlik Sense has a free trial period of 30 days (only in a Qlik account).
  • You can also extend the business trial by 15 days.
  • Qlik Sense business is priced at $30/month per user.

USP:

Qlik Sense takes great pride in enabling users to examine data without a specific query beyond query-based analytics.

Pros:

  • Available via SaaS, the cloud and on premises
  • Integrates with apps such as Dropbox, Microsoft Excel, Hive and Qualtrics
  • Explore predictive calculations in real time

Cons:

  • May require extensive help to set up
  • No dark mode

 

Tableau:

Tableau is a market-leading Business Intelligence tool. Mid-sized to big enterprises employ Tableau, an integrated business intelligence, data analytics, and visualisation tool. It was a 2003 start up with a U.S. basis that Salesforce eventually purchased in 2019.

Product:

  • Tableau Desktop
  • Tableau Server
  • Tableau Online
  • Tableau Reader
  • Tableau Public

Features:

  • Enterprise-grade security surrounds Tableau, preventing data from ever falling into the wrong hands—even while scaling.
  • Tableau skilfully combines and integrates data from several sources, producing a one location for all of your company’s data.
  • The greatest report generating and visualisation capabilities are available in Tableau, and you can quickly share them on the Tableau server.
  • Tableau is a highly dynamic dashboard that accommodates all user ability levels.

Pricing:

  • Tableau boasts of a 14-day free trial version.
  • Tableau Public is a free.
  • Tableau Creator licenses cost $70/month per user.
  • The Explorer license costs $42/month per user.

USP:

Tableau has a wide range of features that promote data integration from any source.

Pros:

  • Offers a free trial
  • Has in-person and virtual conferences (virtual is free)
  • Backed by Salesforce

Cons:

  • No scheduling of reports
  • Its Enterprise solution is more expensive than its competition

 

Knime:

Konstanz Information Miner is most commonly known as KNIME. It is an open-source platform for integrating, analysing, and reporting data. It was initially released in 2006 and used heavily in pharmaceutical research.

Product:

KNIME Analytics Platform – This is open-source and used to clean & gather data, make reusable components accessible to everyone, and create Data Science workflows.

KNIME Server – This is a platform used by enterprises for the deployment of Data Science workflows, team collaboration, management, and automation.

Features:

  • KNIME has a strict software engineering standard to make the software safe for users. The company uses the software to test its security compliance policy.
  • The software’s open-source design allows it to integrate data from all data sources and for all data types.
  • KNIME provides many tools for data visualisation.
  • Creating predictive models or analysis using KNIME’s graphical interface does not require knowledge of programming languages.

Pricing:

  • KNIME software is a free data analysis tool.

USP:

KNIME is an open-source tool that allows you to build or manipulate the software to fit your company goals.

Pros:

  • Doesn’t require prior programming knowledge to use KNIME.
  • Can be created models to deployment and production.

Cons:

  • It is more limited than a programming language
  • The documentation is poor.

 

Zebra BI:

Zebra BI is a service that can be integrated with Power BI and Excel

Product:

  • Zebra BI for PowerPoint
  • Zebra BI for Excel
  • Zebra BI for Power BI

Features:

  • Zebra BI was designed to integrate with Microsoft and is entirely dependent upon Microsoft security regulations.
  • Zebra BI can be imported into Excel immediately because it was designed to operate with it.
  • Zebra BI provides amazing visualisations that place data in its appropriate context. Provide a special report that takes advantage of sophisticated variance charts, difference highlights, etc.
  • Zebra BI is simple to use and doesn’t need any special training or programming experience.

Pricing:

  • Zebra BI has a free version and a pro version.
  • The Zebra BI Pro version costs $4.02/user/month.
  • The pro version also has a 30-day free trial.

USP:

Zebra BI visuals can automatically calculate and visualize data, making report building faster than ever, regardless of data science knowledge.

Pros:

  • It automates a lot and makes it easy to work quickly and get your work done.
  • Very useful for small businesses.
  • One-page dashboard showing the operating results.

Cons:

  • It crashes sometimes or works slowly.

 

 

Looker:

Looker specialises in data discovery and adds value by giving teams new perspectives. It can simply combine with other tools you use because it is a component of the Google Cloud Platform. Additionally, Looker has a strong API that enables you to create unique apps on top of the data it offers. Additionally, you can maintain a multi-cloud data environment and prevent database lock-in thanks to its support for several SQL dialects.

Product

  • Business Intelligence
  • Embedded Analytics

Features:

  • Looker offers enterprise-class security. This implies that you may regulate and restrict user-level access to data.
  • Over 60 SQL data sources, such as Oracle and Google Big Query, are included in the data integration. You may access the database and insert SQL using Looker.
  • The possibilities of data visualisation are endless. In addition to pre-made templates, you may create unique graphics.
  • Looker offers a dynamic and interactive dashboard that enables you to analyse in-depth data.

Pricing:

  • Looker supports a demo version on request.
  • Free trials are available.
  • Looker Enterprise can cost up to $5,000 per month.

USP:

Looker provides embedded analytics for users, speeding up the creation of data-driven applications.

Pros:

  • Part of the Google Cloud Platform
  • Supports more than 50 SQL dialects
  • Create custom apps
  • Offers a free trial

Cons:

  • Charged the full price for users who only need read access
  • Steep learning curve

 

SAS Business Intelligence:

Statistical Analysis System (SAS) is a statistical software suite used to manage and perform in-depth data analysis. This data analysis tool was released over 50 years ago and is currently very much in use.

Products:

  • SAS® Enterprise Guide®
  • SAS® Office Analytics
  • SAS® Visual Analytics

Features:

  • The GDPR compliance of the SAS software security architecture is maintained while using best practises in data security and privacy.
  • When it comes to data collecting and sharing of insights, SAS is effectively integrated with other programmes and databases.
  • SAS enables you to produce eye-catching visualisations that facilitate quick comprehension of a data collection.
  • SAS is simple to use for everyone thanks to its drag-and-drop functionality and mobile editions.

Pricing:

  • SAS costs start at $8,000 per year for businesses.
  • SAS offers free trials and demo versions lasting an average of 30 days.

USP:

SAS is a complete package that can be used in data analysis, from basic statistics to advanced data analysis.

Pros:

  • Provides the flexibility to the end user to slice and dice the data.
  • Anyone can make predictive models with the help of in-built algorithms without the need to write a single line of code or knowledge of what’s under the hood of algorithms.
  • The feature to ask a question related to data and get a response in text, chart, or graph is amazing.

Cons:

  • SAS Business Intelligence is very expensive.
  • There is a steep learning curve to be proficient at using SAS Business Intelligence, even for people experienced with BASE SAS.
  • Limited functionality

 

Apache Superset:

A contemporary tool for data exploration and visualisation is Apache Superset. It is a big data handling open-source software application tool.

Products:

The recent version is 2.4.5 and 3.0.0 is in preview.

Features:

  • With the help of Superset, various users may be given access to different levels of data.
  • Any database or data source that uses structured query language (SQL) may be connected to using Apache Superset and have its data integrated.
  • Superset provides a large selection of detailed visualisation models. You can create unique visuals and then import them into Superset using the visualisation plug-in.
  • Interactive dashboards from Apache Superset make retrieving and viewing data simple.

Pricing:

Apache Superset is free to use.

USP:

Apache Superset is an open-source software application that one can modify to suit a company’s needs. It is among the few data analysis tools available to handle big data.

Pros:

  • Free software.
  • Many pre-built visuals are available.
  • Incorporate the dashboards into your data apps using Apache Superset.
  • incredible community (I was able to get super fast support on a weekend).
  • architecture for a simple web server.
  • User access control with granularity.
  • Based on the OpenAPI specification, the Rest API.

Cons:

  • Charts and exploration sections cannot be joined. The dataset must either be a view or pre-joined.
  • Users must be familiar with SQL. Engineers can assist with view creation and other tasks. End users will need to be familiar with SQL for the BI tool to be completely self-serving.
  • Management might be challenging if strong dev ops and data team are absent. The managed version from the preset unless you get it.

 

GoodData:

A U.S.-based software provider called GoodData offers infrastructure for data analysis. Over 30 000 enterprises are presently served by the company, which was founded in 2007.

Products:

 

Features:

  • Standard security is provided by GoodData for all plans, and enhanced enterprise security is provided for the enterprise plan.
  • Among other sources, GoodData connects with databases, data warehouses, and manually submitted CSV files.
  • You may quickly share reports with colleagues using GoodData and view data using charts.
  • For various devices, GoodData analytics is well-optimized.

Pricing:

  • The Growth of GoodData plan costs $20/month per workspace.
  • The Enterprise plan has custom pricing.

USP:

The GoodData analytics platform can be used to embed dashboards with options for coding and no coding.

Pros:

  • It’s a good platform with a flexible pricing structure, allowing users to start out with hands-free service.
  • Excellent charts and drill-down analysis that GoodData offers its users makes complex large data sets simple and simple to understand and interpret.

Cons:

  • It’s missing some key features compared to Tableau.
  • The platform here is not for data scientists.
  • Inability to keep their workspaces and dashboards’ code versions up to date
  • only a few secure information transfer methods between your system and theirs.

 

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