Data Analysis Software

An endless amount of data is available to work with, as the world is becoming more data-driven. Organizations can make better business decisions with data analytics as they provide valuable insights, which in turn helps them make the right choices for their current and future business projects.

What is data analysis software?

Data analysis software is a system that enables users with the process of cleaning, inspecting, transforming, and modeling data to discover meaningful information for better decision making 

How to select the best data analysis software?

Picking the best data analysis tool is a bit challenging. To ease this, it would be great to check the following list of best data analysis software formulated by GoodFirms. Every software listed below also comes with its core functionalities, prices, and reviews from its buyers. 

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List of Best Data Analysis Tool

  • 1. Keen

    The Complete Event Data Streaming Platform
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    Keen.io is the complete event data streaming platform. Our platform can handle all aspects of your event data management, from collection to application. Stream, store, query, and present your data all in one place and get a competitive advantage over the competition. Keen allows you to get a true view of your product usage and interaction through event-based data. We make it easy to dive into the... learn more about Keen

    Entry Level Price
    $149 Per Month
    Free Trial
    30 Days
    50%

    Category Focus

    Data Analysis Software
  • 2. Zoho Analytics

    Transform your business with powerful insights.
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    Zoho Analytics is a self-service BI and data analytics software that lets you create visually appealing data visualizations and insightful dashboards in minutes.   ... learn more about Zoho Analytics

    "The best part is that it is easy to share lightweight consumer data at a low cost"
    Melissa Terry, CFA at VEM-Tooling
    Entry Level Price
    $30.00 Per Month
    Free Trial
    15 Days
    20%

    Category Focus

    Data Analysis Software
  • 3. Qlik Sense

    Go from passive to active analytics
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    Qlik Sense is world-class business intelligence software that helps global enterprises move faster, work smarter, and put modern analytics in everyone's hands. Easily combine load, visualize and explore data, no matter how large (or small). Create and share powerful, interactive dashboards in a governable environment. Get unmatched performance and scalability on enterprise SaaS, your cloud of choi... learn more about Qlik Sense

    "Simply intelligent software for business data analysis, calculation, and reporting"
    Ronald Williams, Founder at BestPeopleFinder
    Entry Level Price
    $30 Per Month
    Free Trial
    30 Days
    25%

    Category Focus

    Data Analysis Software
  • 4. Google Data Studio

    Your data is beautiful. Use it.
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    Google Data Studio turns your data into fully customizable informative reports and dashboards that are easy to read and share. Unlock the power of your data with interactive dashboards and beautiful reports.... learn more about Google Data Studio

    "The tool is very flexible and you can customize it to your needs in many different ways"
    Rafał Młodzki, CEO at Passport-Photo Online
    Entry Level Price
    Free version
    Free Trial
    Available
    25%

    Category Focus

    Data Analysis Software
  • 5. Stata

    For Statistics and Data Science
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    Stata is the solution for your data science needs. Obtain and manipulate data. Explore. Visualize. Model. Make inferences. Collect your results in reproducible reports. ... learn more about Stata

    "It is a complete statistical answer for every field and all kind of statistical analysis are all feasible "
    Shiv Gupta, CEO at Incrementors Inbound Marketing
    Entry Level Price
    Contact Vendor
    Free Trial
    30 Days
    50%

    Category Focus

    Data Analysis Software
  • 6. Minitab

    Powerful statistical software.
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    Minitab provides convenient features that streamline your workflow, a comprehensive set of statistics for exploring your data, and graphs for communicating your success. ... learn more about Minitab

    "Minitab contributes a lot in the decision making process "
    Shiv Gupta, CEO at Incrementors Inbound Marketing
    Entry Level Price
    Contact Vendor
    Free Trial
    30 Days
    50%

    Category Focus

    Data Analysis Software
  • 7. DQLabs

    Modern Data Quality-centric Observability platform
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    DQLabs.ai is a Modern Data Quality-centric Observability platform for enterprises to deliver data relevance. With an Automation first approach powered by self-learning capabilities, organizations can not only observe but also measure, and remediate data quality issues to improve business outcomes.... learn more about DQLabs

    "An excellent data quality platform for automation"
    Indhu
    Entry Level Price
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    Free Trial
    N/A
    0%

    Category Focus

    Data Analysis Software
  • 8. RapidMiner Studio

    Comprehensive data science platform with visual workflow design and full automation
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    RapidMiner Studio is a visual data science workflow designer accelerating the prototyping & validation of models. Easy to use visual environment for building analytics processes: Graphical design environment makes it simple and fast to design better models.... learn more about RapidMiner Studio

    "Exceptionally Intuitive tool!"
    Donald Wilde
    Entry Level Price
    Free version
    Free Trial
    Available
    33%

    Category Focus

    Data Analysis Software
  • 9. SAS Viya

    Confident decisions at every moment.
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    SAS Viya is an AI, analytic, and data management platform that runs on modern, scalable architecture. Quickly transform raw data into operational insights that support every kind of decision your organization makes. Better decisions, maximum value, faster outcomes. That's the SAS Viya difference. SAS Viya enables users to quickly transform raw data into operational insights that support every kind... learn more about SAS Viya

    "Best software for small business!"
    Rex Freiberger, CEO at Gadget Review
    Entry Level Price
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    Free Trial
    14 Days
    33%

    Category Focus

    Data Analysis Software
  • 10. Mode

    Interactive data science meets modern BI
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    Mode is an analytics platform designed to help data analysts and data scientists analyze, visualize, and share data. Run fast, advanced analysis by seamlessly switching between a cloud-based SQL Editor, Python & R notebooks, and interactive visualizations. Focus on analysis, while stakeholders self-serve.... learn more about Mode

    "Mode works very well."
    Prashant Sugand, Director & Principal Consultant at Layertech
    Entry Level Price
    Contact Vendor
    Free Trial
    N/A
    33%

    Category Focus

    Data Analysis Software
  • 11. JMP

    Data analysis software
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    JMP is the data analysis tool of choice for hundreds of thousands of scientists, engineers and other data explorers worldwide. Users leverage powerful statistical and analytic capabilities in JMP to discover the unexpected. ... learn more about JMP

    "It has got you covered in all manners that will wow your stakeholders and key decision-makers. "
    Shiv Gupta, CEO at Incrementors Inbound Marketing
    Entry Level Price
    Contact Vendor
    Free Trial
    30 Days
    33%

    Category Focus

    Data Analysis Software
  • 12. GoodData

    The Leader in Embedded Analytics & Intelligence.
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    GoodData powers the transformation of decision-making for frontline workers within their daily business processes. It's a platform that gathers data and user decisions and transforms them into actionable insights delivered at the point of work. This empowers enterprises and software companies to integrate insights into applications so that their customers, partners, and employees can make more... learn more about GoodData

    "Best for user data visualization session"
    Moe Bahidra
    Entry Level Price
    Contact Vendor
    Free Trial
    30 Days
    50%

    Category Focus

    Data Analysis Software
  • Whether you want to instantly deliver personalized reports to thousands of users, empower business users with self-service analytics, or boost analytics adoption to 100% across your enterprise, MicroStrategy provides the technology to make it happen. MicroStrategy's powerful analytical engine, comprehensive toolsets, variety of data connectors, and scalable, open architecture ensure you have every... learn more about MicroStrategy Enterprise Analytics

    "It has got the highest level of stability and safety"
    Gerrid Smith, Chief marketing officer at Joy Organics
    Entry Level Price
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    Free Trial
    N/A
    20%

    Category Focus

    Data Analysis Software
  • 14. OriginPro

    Data Analysis and Graphing Software
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    Origin is the data analysis and graphing software of choice for over half a million scientists and engineers in commercial industries, academia, and government laboratories worldwide. Origin offers an easy-to-use interface for beginners, combined with the ability to perform advanced customization as you become more familiar with the application. Take your data analysis to the next level with Origi... learn more about OriginPro

    "OriginPro is ready-to-use with the best visualization as well as provides us with a better understanding of statistics"
    Ryan Yount, Founder at LuckLuckGo
    Entry Level Price
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    Free Trial
    Available
    100%

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    Data Analysis Software
  • 15. Wolfram Mathematica

    The world's definitive system for modern technical computing
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    Widely admired for both its technical prowess and elegant ease of use, Mathematica provides a single integrated, continually expanding system that covers the breadth and depth of technical computing—and seamlessly available in the cloud through any web browser, as well as natively on all modern desktop systems.... learn more about Wolfram Mathematica

    "Mathematica is the go-to software and recent favorite that deserves attention"
    Marcin Bartoszek, Head Of Business Intelligence at Spacelift
    Entry Level Price
    $1490 Per Year
    Free Trial
    15 Days
    25%

    Category Focus

    Data Analysis Software
  • 16. XLSTAT

    Your data analysis solution
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    The XLSTAT statistical analysis add-in offers a wide variety of functions to enhance the analytical capabilities of Excel, making it the ideal tool for your everyday data analysis and statistics requirements. ... learn more about XLSTAT

    Entry Level Price
    Contact Vendor
    Free Trial
    14 Days
    50%

    Category Focus

    Data Analysis Software
  • 17. KNIME Analytics Platform

    End to end data science for better decision making.
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    KNIME Analytics Platform is the open source software for creating data science applications and services. Intuitive, open, and continuously integrating new developments, KNIME makes understanding data and designing data science workflows and reusable components accessible to everyone. ... learn more about KNIME Analytics Platform

    Entry Level Price
    Free version
    Free Trial
    Available
    33%

    Category Focus

    Data Analysis Software
  • 18. KNOWAGE

    Modern business intelligence and advanced analysis.
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    Knowage offers FULL ANALYTICAL CAPABILITIES, with a special focus on big data analytics and comprehensive support to rich and multi-source data analysis. Knowage provides different modules, each one focused on a specific domain but mutually combinable (Big Data, Smart Intelligence, Enterprise Reporting, Location Intelligence, Performance Management, Predictive Analysis). It is available in two ve... learn more about KNOWAGE

    Entry Level Price
    Free version
    Free Trial
    Available
    33%

    Category Focus

    Data Analysis Software
  • 19. Grafana

    The open observability platform
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    Data visualization & Monitoring with support for Graphite, InfluxDB, Prometheus, Elasticsearch and many more databases. Beautiful metric & analytic dashboards more!... learn more about Grafana

    Entry Level Price
    Free version
    Free Trial
    Available
    50%

    Category Focus

    Data Analysis Software
  • 20. Parse.ly

    Make your content perform better. Instantly.
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    Parse.ly is the new measure of content value. Do you work in content marketing, digital media, audience development, corporate communications, or any other role in which your company's content is central to business goals and audience growth? If so, you want a way to win with your content. And Parse.ly can help. ... learn more about Parse.ly

    Entry Level Price
    $500 Per Month
    Free Trial
    30 Days
    50%

    Category Focus

    Data Analysis Software
  • 21. Kissmetrics

    ADVANCED BEHAVIORAL WEB ANALYTICS
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    The best tool for product and marketing teams – accelerate website growth today with Kissmetrics. Move past unreliable session-based analytics like GA into advanced user-based insights. Great product, great service, great price. Let us show you how today! ... learn more about Kissmetrics

    Entry Level Price
    $299 Per Month
    Free Trial
    N/A
    50%

    Category Focus

    Data Analysis Software
  • 22. Cluvio

    Listen to your data
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    Cluvio is a modern data analytics platform that lets you run SQL queries against your database, process data in R, visualize the results and create beautiful, interactive dashboards in minutes. With pricing optimized for startups and small companies, it is easy and cost effective to share insights with everyone in your company or your customers. Cluvio also supports powerful embedding that allows ... learn more about Cluvio

    Entry Level Price
    Free version
    Free Trial
    Available
    33%

    Category Focus

    Data Analysis Software
  • 23. Spider Impact

    Amp Up Your Strategy.
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    Spider Impact is performance management software that powers data visualization, balanced scorecards, team alignment, and KPI and initiative management. Don't just define your strategy—live it. Get on-demand performance data from any perspective you desire. Allow employees to see and understand their roles in organizational success. Define and track your strategic initiatives at all levels of th... learn more about Spider Impact

    Entry Level Price
    $125 Per Month
    Free Trial
    N/A
    25%

    Category Focus

    Data Analysis Software
  • 24. AnswerDock

    Ask Questions About Your Data & Get Instant Answers
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    Answer dock is a data analytics company that uses Natural Language Processing (NLP) with Artificial Intelligence (AI) to empower business users to make smarter data-driven decisions. Our mission is to create an easy to use analytics product that speaks the business users’ language and enables them to leverage powerful analysis techniques and algorithms, without the need for data analysts or s... learn more about AnswerDock

    Entry Level Price
    Free version
    Free Trial
    Available
    33%

    Category Focus

    Data Analysis Software
  • 25. Solver Suite

    For organizations looking to grow and gain complete insight into their business
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    Helping organizations grow and gain complete insight into their business Solver, Inc. is redefining the category of cloud-based reporting and planning. The Solver solution is built to enable faster and better business decisions across the entire organization. Solver combines financial and other key data into a single tool, powered by the most flexible report and planning form designer on the mark... learn more about Solver Suite

    Entry Level Price
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    N/A
    25%

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    Data Analysis Software
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Buyer’s Guide

Introduction to the buyer’s guide for data analysis software:

Do you remember Michael Burry? The critically acclaimed film on financial markets- The Big Short is based on this legendary hedge fund manager's life. He successfully predicted the US housing loan bubble of 2007-2008 that triggered the economic depression of 2008. How was he able to do that? By analyzing the mortgage lending data from 2003 to 2004. When the whole S&P index rose only 3% between 2000 and 2008, the funds managed by Michael Burry returned a whopping 489.34% during the same period.  That's the power of data analysis. For the hundreds of decisions organizations make every day, data analysis provides a mechanism to identify patterns, anticipate results, and respond proactively. 

Today's businesses are luckier than Michael, as what he did manually can be done through a click of the button using a Data Analysis Software.  The data analysis technology has advanced dramatically in the past decade and has taken a leap forward with more sophisticated algorithms and massive data processing capabilities. However, deploying the right technology that provides businesses with functional expertise to use data is the biggest challenge that companies face. 

This buyer's guide attempts to guide businesses in making the right decision to invest in the best data analysis software by providing them a comprehensive view of all aspects of a data analysis software such as features, use, pricing, and types. 

What is data analysis?

Data analysis is the process and technique of analyzing data to draw conclusions, get insights, and highlight the most useful part of the raw data. Data analysis involves cleaning and modeling data to unearth critical information for business decision-making. Today, mechanical processes, preset algorithms, and software applications are used to process the data for analysis. 

Types of Data Analysis Methods:

Descriptive Data Analysis:

Descriptive data analysis, a part of statistical data analysis, focuses on past data such as profits, revenues, sales, KPIs, etc. to reveal meaningful insights about the business's performance over time. Companies often visualize their earnings and revenues over the past years (Quarterly, Yearly Reports) with trendlines formed with descriptive data analysis methods.

Diagnostic Data Analysis:

Diagnostic data analysis is the process of identifying behavior patterns and relating them with a recent business phenomenon. For example, if sales increased dramatically in a particular month, then a business may use diagnostic data analysis to determine the factors that caused the sudden surge. If a business finds out that sales data corresponded with the increased marketing spend prior to the sales surge month, then they can decide if they should increase the marketing budget for the coming months too.  

Predictive Data Analysis:

Predictive data analysis predicts future trends, events, revenues, etc. based on the current and past data analysis. For example, a company studies past ten-year sales data and finds that sales are generally down in April-May months. Based on such data, the company can revise their inventory needs for next year's May and June. 

Prescriptive Data Analysis:

Prescriptive data analysis utilizes the results of above all analysis to form a conclusive strategy to mitigate a challenge or decide on the future course of action. 

Why do businesses need data analysis?

Consider the following business scenarios:

  1. A manufacturer  to launch a new product in the overseas market
  2. A pharma company wants to apply for new drug approval with the FDA.
  3. A sales manager wants to know the reason for the product's poor performance in a particular location.

In all the above situations, data analysis is essential. The company will have to analyze the market data for a response to such products in the overseas market, the pharma company will have to rely on trial test results and its analysis before applying, and the sales manager will have to carry out a detailed analysis of the customer preference and buying behavior survey to find the reason for poor performance. Data analysis is the lifeline of businesses. 

As businesses around the world get smarter, data-driven insights become the key to competitive advantage. Web, sensors, phone transactions, cameras, POS systems, etc. create a huge array of data sets for businesses that can be used for valuable analytics. Data-driven insights enable companies to better target the market compared to their competitors.

Key terminology associated with the data analysis process:

​​​​​​Data set

The data set is the collection of data represented in rows and columns (Units of observation). Data itself is a plural form of datum. For example, you can observe toys and infer a set of characteristics such as size, color, price, shape, etc. If such patterns and differences are put into rows and columns to present the information about those toys, it will be called a data set. 

Data source

In the technological sense, data source refers to the location from which data originates. For example, a company may store the names, email addresses, purchasing history, contact details, preferences, etc. of customers in a CRM database. In this case, the database containing customer data is the data source. Data can be retrieved whenever required from its source through web accessibility or local server connection. 

Database

It is the collection of structured data. It usually consists of organized sets of information that can be retrieved and updated as required.  There are many types of databases based on their operation. For example, Relational databases such as MySQL, Oracle, Sybase, and more use the standard language SQL (Structured Query Language) for searching, inserting and updating databases. Another type,  NoSQL database, is used to store unstructured data. Nowadays, advanced Cloud databases with massive storage capacities and support to various software applications are deployed by businesses. According to Gartner, by 2022, cloud services will be essential for 90% of data and analytics innovation.

Data blending

In the data blending process, data analysts collect data from various sources and combine them to form a useful functioning data set. Data blending is done to improve the quality, functionality, and utility of data. The blended data can reveal more profound insights into the data and drive better analysis. Businesses that imbibe predictive analytics into their core functions often rely on data blending for higher intelligence. 

Qualitative data

Qualitative data refers to data collected in a descriptive or categorical form. It is the data that cannot be computed by can be put in a verbal or narrative form. It is not measurable and exploratory in nature. For example, opinion interviews, case studies, expert opinions, open-ended questions, etc. can get you qualitative data. 

Quantitative data

Quantitative data refers to data collected in numerical units. It is measurable and conclusive. In short, this data can be analyzed statistically and often provides information about the level of occurrence of some entity. For instance, responses from the Likert scale can get you quantitative data.  

Data Alerts

Data alerts are email notifications or message alerts that one gets when data changes or data levels reach a pre-specified condition. Data alerts are helpful to businesses when a huge amount of data is monitored on a day to day basis, and businesses don't want to miss out on vital data changes.

Data visualization

Data visualization is the technique to represent data in visual graphics form by using elements such as charts, graphs, and maps, etc. Data visualization helps to see the trends and patterns in any data set clearly and in an easily comprehensible manner. 

Data points

Datapoint is a unit of information, a single fact, an individual item, in the data that is being analyzed. Multiple data points create charts or trend lines.

Metadata

Metadata is the data that summarizes information about other data. Metadata is a useful tool for finding and extracting relevant information from a huge dataset. Metadata usually provides information such as title, keywords, themes, context, and utility of the data. 

Big data analytics

Big data analysis is the method of harnessing and analyzing a large amount of data for unearthing patterns, correlations, and hidden value in the massive data. Businesses use big data analytics for faster decision making, gauging ideas for rolling out new products and services, and gain competitive advantage by data-fuelled insights. Most of the Big data is generated from sensors, devices, transactions, web, and social media. 

Granular data

Granular data is the data that is derived from dividing large data into sub-divisions. For obtaining granular data, data is divided into the lowest possible extent. It helps data analysts to be more specific in confirming data facts. 

Data Mining

Data mining is done to discover patterns in large data sets using artificial intelligence and machine learning. 

Data Analysis Process: Then and Now. How has the data analysis process changed over time?

Data analysis has played a crucial role in the progress that human civilizations have made so far. The inscriptions on walls and caves were analyzed to learn about our history and ancient languages. Whatever we know about the world today, the solar system, the galaxies, etc. are possible due to data analysis. When Henry Ford measured the speed of assembly lines to increase the production of cars, he was using data analysis. W.D Gann, the legendary trader, studied data of the past 1000 years of wheat and accurately predicted that wheat would sell at $1.20 in September 1909. He also used data analysis. (Source-Ticker and Investment book by Richard D. Wykoff). 

Data is everywhere, and humans have relied on data for many of their accomplishments. The data process evolved with time, and today most of it is automated and carried out by software applications. 

Let us discuss the data analysis process in detail. The process involved in data analysis involves several different steps:

Step 1: Defining data prerequisites:

Before one goes for data analysis, one has to define the prerequisites for the data analysis process clearly:

  • The questions for the data analysis: One must know why the data needs analysis? Clearly define the questions for which the answers are required.
  • Data segregation points: One needs to identify how data will be grouped? List down the parameters for data grouping such as age, demographics, categories, colors, size, etc.
  • Method: Deciding which method will be used for analysis is also critical.
  • Time Frame: One needs to decide the time frame for which the data will be analyzed.

Step 2: Data collection:

Once the prerequisites are met, one needs to collect data using data collection methods such as:

  • Getting data from already existing databases such as CRM database, inventory database, sales data, ledgers, bank statements, etc.
  • One can also gather data through interviews, case studies, questionnaires, surveys, polls, expert opinions, website analytics, customer reviews, etc.

Step 3: Data Cleansing

Data cleansing or data cleaning method is the process to get rid of irrelevant, duplicate, inaccurate and incomplete data that is not required for data analysis. Data cleaning makes the data error-free and brings accuracy and precision in the final results. 

Step 4: Data Processing

This step processes the data and analyzes it for various correlations, trends, and combinations to deliver valuable insights about the data. This is a very crucial step in the data analysis process, and generally, businesses use advanced data analytics tools to complete this step.  Data visualization feature is used in this step to make the data analysis easy to understand. 

Step 5: Data Interpretation

This is the final step of data analysis. The analyzed data is set for meaningful conclusions, findings, and interpretations. Data is interpreted for valuable analytics and solutions that can be applied for future action based on the data analysis results. 

What are the challenges faced in data analysis?

  • Collecting real-time data
  • Getting rid of outdated data 
  • Presenting data in an understandable format
  • Managing data from multiple sources
  • Dealing with poor quality data
  • Conducting data analysis accurately
  • Shortage of skilled data analysts
  • Maintaining the security and privacy of the organizational data
  • Sharing the analytics in real-time with team members
  • Another challenge is to incorporate data-driven insights into daily workflows 


 



 

What is data analysis software?

Data analysis software is an application that helps in collecting, merging, cleaning, analyzing, and interpreting data.  It also has features to present data in a visually appealing format. Data analysis software is used by managers, data scientists, statistical analysts, data analysts, etc. for reliable data analysis and insights. 

What are the different types of data analysis software?

Desktop-based/On-Premise 

These types of data analysis software solutions are licensed, and businesses can install them within their IT infrastructure. On-Premise, data analytics systems are highly customizable in nature.  

Web-based

These types of online data analysis software are hosted, and third-party data analysis solution providers offer these tools. Web-based online data analysis tools are very popular applications as they don’t require any hardware installation and can run online with a login ID and internet connectivity. 

Cloud-based

These types of data analysis software solutions are hosted through third-party cloud service providers. These are popular with large organizations that require big data analytics, massive data storage capacity, and extreme flexibility. 

Open Source

These types of data analysis software allow users to customize the source code, alter inbuilt settings, and modify functions by adding extra plugins. When organizations need tailored solutions that are unavailable with any vendor, then open source data analysis software can be opted. 



 

What are the benefits of data analysis software?

Data analysis software has the features to carry all the steps of the data analysis process.  Apart from this, the other benefits are:

Timely decision making:

Unlocking the potential value of data requires analytics. Businesses can improve their knowledge and understanding of business processes, customers, campaigns, products, finances, employees, etc. through data analysis processes. Businesses can unveil the value hidden in data with the help of a data analysis software that removes the guesswork and provides key metrics required for better decision making. Data analysis software helps organizations make reliable decisions to meet customer expectations, mitigate global challenges, and stay competitive.

Provides valuable insights:

Without insights, data is of no use. Organizations that know what to do with data can capitalize it for long-term success.  Continuous data analysis with real-time data provides businesses space and time to tailor services, alter campaigns, modify strategies, and optimize current processes to improve results. 

Storing and retrieving data easily:

With quintillions Gigabytes of data produced every year in the world, storing and retrieving data from multiple sources and databases is a challenging task. Pre-planned data analysis programs with the help of analytics software make it easy to store and retrieve data. Data analytics applications support all types of databases and integrate with them smoothly to import data whenever required.  

Optimizes various businesses activities:

Using a business analysis tool, various critical business activities such as budgeting, hiring, scheduling, advertising, inventory management, customer service, etc. can be optimized and improved.

Proper planning and execution: 

Data software helps managers plan their course of action realistically and more accurately by providing essential information about the resources and time. Managers can forecast future actions from multiple perspectives and create a flexible but effective strategy that is easy to execute. 

Saves Time:

The amount of data that current-day businesses generate daily is too huge to manage manually. It is humanly not possible to study the data manually for insights. Therefore, data analysis software rescues managers from menial responsibilities and empowers them to use the data analysis application's insights directly.

Solves problems and eliminates errors:

Many times, businesses face issues of data mismatch, fraudulent transactions, errors in processes, etc. A robust data analysis software can help businesses to identify the leakages by analyzing the granular data.

What are the key features of data analysis software?

Importing data

Data analysis software allows users to import data from various file formats such as CSV, excel sheets, HTML, etc. to the software for analysis. You can also import data from these sources to tables of the data analysis software. The data analysis software supports all types of databases, including NoSQL and SQL databases. Data stored in cloud servers or local databases can also be imported. 

Data synchronization

For regular data analysis, users can set periodic or real-time synchronization of the data between the data analysis software and the database of their choice. By enabling real-time synchronization, data will get uploaded to analytics software automatically.  

Importing data from popular applications

Most advanced data analysis software supports popular business applications such as CRM, Sales, Marketing, Project Management, etc. for direct database collaboration and faster analysis. 

Data blending

Data analysis software allows users to merge data from two applications or sources to create meaningful results. 

Data Visualization tools

Data analysis software has inbuilt data visualization tools to make a variety of charts, pivot tables widgets, graphs, tables, etc.  It also creates insightful reports and custom dashboards with the intuitive drag and drop interface. Other options, such as insert images, format text, create a design layout, drill-downs, contextual filters, and many more, help in visualizing data effectively. Some data analysis software come with interactive map integration to visualize your data geographically. 

Various analytics and reporting tools

Data analysis software is capable of in-depth analysis of various metrics and key performance indicators. It comes with extensive analytical capabilities and core functions such as forecasting, projection, and reporting.

Sharing and collaboration

Data analysis software enables managers to share real-time data analytics with their team for informed decision making and teamwork. 

Data security tools

Data analysis software comes with inbuilt encryption, firewalls, regular backups, etc. features for security and data usage privacy. 

Other Features: 

  • Set Data alerts
  • Set access control
  • Inbuilt business intelligence

What are the current trends in the data analysis field?

Augmented analytics

Augmented analytics uses machine learning, NLP (Neurolinguistics Programming), and artificial intelligence to gather business analytics. Augmented analytics produces faster results, deeper insights, and speedy visualization. 

Conversational analytics

Conversational analytics uses processes such as textual data mining, sentiment analysis, and social listening to derive insights about consumer behavior and satisfaction.

Data-Driven Culture

Incorporating data-driven culture into organizations is an important trend in the data analytics world. Business Intelligence professionals and managers are prioritizing the implementation of a culture where decisions are based on data-driven insights.  

Data Analysis Automation

Organizations are implementing automated processes to handle massive data sets. Automated data analysis and automated decision making are popular trends in data analytics

Graph analytics

Graph analytics is the process of analyzing data in a graph format. It requires managers to analyze data with a database platform that supports graphs format. Graph analytics is getting traction for solving complex problems. Graph analytics is used for revealing relationships between logical concepts and people, organizations, and related entities. 

Continuous Intelligence

Continuous intelligence (CI) uses real-time data to enable automated decision-making. This technique generates continuous insights and real-time analytics for decision-making. In June 2020, when oil prices went below zero levels, most of the data analysis systems struggled to make trading decisions as data analysts never thought that oil could go below zero levels. In such scenarios, a continuous intelligence method has a greater advantage over other data feeding algorithms as it continuously updates its data feeds to automatically make real-time decisions. 

Big data analytics

With billions of connected devices, the data created by these is massive and overwhelming. Big data analytics attempts to map this data for meaningful insights. There is a growing trend among organizations to utilize big data for providing personalized services to their customers.

What is the role of data analysis software in various industries?

Financial Sector

Banks and NBFCs can deploy data analytics software to become hyper-intelligent organizations that provide personalized customer experiences and complete regulatory compliance for its services. Data analysis helps financial organizations in the early detection of frauds, risk management, operational excellence, and increasing engagement with customers through personalized offers. Even Insurance and Mutual funds companies can provide personalized offers to their clients based on their preferences. The financial sector can use big data analytics to predict future market trends. 

Healthcare

Data integration and systematic analysis of data with the help of data analytics software enable improved clinical decisions. It also helps prevent healthcare financial frauds and improves patient satisfaction.  Data analysis of various medical, and wearables devices such as Fitbits helps physicians to monitor their patient's health remotely based on the analysis of data received from these devices.  

Manufacturing

Manufacturing data analytics solutions enable managers to balance production operations for cost reduction and risk management. In manufacturing, advanced analytics helps operations managers gain insights from historical processes to optimize the current ones for better yields. Companies can also capitalize on big data to optimize their manufacturing cycles. 

Retail 

Data analysis software can be used to optimize retail operations, merchandise planning, controlling the supply chain, and making the customer journey a pleasant experience. Using past data, big data analytics, and AI, retail businesses can predict customers' future behavior, develop personalized marketing campaigns, and improve employee training. 

Education

Educational institutes can improve learning environments, teaching techniques, and learning outcomes by deploying data analytics techniques. Data received from students' feedback, parents' feedback, evaluation, results, etc. can be analyzed to improve the learning process and reduce dropout rates. 

Logistics and Transportation

Data analysis enables Transportation and Logistics Companies to understand the reasons behind shipping delays and performance across various shipping routes. Using such insights, logistics companies can optimize delivery times and reduce costs. 

 How to choose the best data analysis software for your business?

Finding a data analysis solution that provides real-time insights, valuable metrics, and comprehensive services will surely make a difference to your business. The type of data analysis software solution can vary from business to business based on your requirements. However, there are a number of crucial factors to consider before investing in the right data analysis software solution. Hence, before you select a particular data analysis tool, make sure that it is capable of answering all below questions in an affirmative:
  • Does it provide all features, functionality, integrations, and settings for your analysis needs? 
  • Is the data analysis software user-friendly? 
  • Can you customize the data analysis software or request to add more functions over time?
  • Does the data analytics application deploy advanced security features such as encryption, firewall, access controls, backup plans, etc. ?
  • Can it work with all types of databases to retrieve your data?
  • Is your data analysis software vendor well-experienced in the data analysis field?
  • Does the software provider offer a free trial/free demo of its services?
  • Are you going to get free live training/demo or customer support services from the software provider?

If the answer is 'yes' to above all questions, then you have all green ticks to go ahead and purchase the software. 

What is the average cost of buying data analysis software?

The costs of the data analysis system depend on a large number of factors such as:

  • The number of users
  • Features and functions it offers
  • The amount of data it can process in a given time frame
  • The maximum data analyzing capacity
  • Quality of service offered 
  • Integrations it offers
  • User interface and experience

These variations can change the cost factor and estimations of the data analysis software significantly.  

The enterprise version of Qlik Sense will cost you $70 a month per user, while the basic version is available for $30 per user per month. Parse.ly data analysis software will cost $1500 per month for its Growth plan and $500 per month for the Starter plan. Freemium data analysis software such as Cluvio comes with a free version for single users with a maximum of three dashboards. Zoho Analytics also offers a freemium version with a free plan for two users, while enterprise plans for 50 users will cost $495.  If you need more free data analysis software, try Anaconda, Kyubit, AnswerDock, and MeMSQL

For other online data analysis tools such as SAS, Stata, Solver Suite, WebFocus, you need to contact the vendor for detailed pricing. You can get the list and all information from the GoodFirms data analysis software Page.


 

Why refer to GoodFirms’ list of data analysis software?

Goodfirms is a leading IT  research company renowned in the IT field for its database of thousands of IT services and products. GoodFirms has an impressive track record of providing buying support and assistance to B2B IT service seekers. GoodFirms researches, creates, organizes, and regularly updates the huge database of software services and products. It lists companies and their products based on their performance, features, functionalities,  updates, pricings, and user reviews. Currently, GoodFirms houses a massive list of 60000+ software products and services. GoodFirms has also received 30000+ reviews of these services and products from verified users. You are advised to go through the extensively researched best data analysis software list to find the best suitable one for yourself. You can filter the data analysis software solutions based on various criteria such as features, deployment type, pricings, and many more. You can also read reviews to have better insights about software services. 

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