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What is Data Analytics Software?
Data analytics software is used for quantitative and qualitative analysis of business data to boost productivity and profits. With data analytics software, businesses can extract and categorize data, and identify and analyze patterns and behaviors to gain insight. Global enterprises collect and analyze data related to practical experience, market economics, business processes, and customers. This data is stored and analyzed to learn buying patterns and trends, and the insight thus obtained is utilized to make smarter decisions. For instance, a social networking site can collect user data and use data analytics software to learn key customer trends that they can utilize to enhance their layout, content, and overall strategies. Start by checking our leader HubSpot Marketing Hub, and other recommended solutions in this category.
How was this ranking made?
In order to create this ranking of best Data Analytics Software we have checked 314 trending tools currently available on the market, analyzing their features, ease-of-use, client support, possible integrations and mobile support using our unique SmartScoreTM rating algorithm. This ranking has been developed by Jenny Chang, our SaaS expert responsible for the Data Analytics Software category.
List of Top 18 Data Analytics Software
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- Score
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1. HubSpot Marketing Hub
Our score: 9.5 User satisfaction: 98%HubSpot Marketing is an easy-to-use advanced digital marketing software solution. It is used for a variety of marketing needs and channels from SEO to social media. The platform has a CRM base complete with analytics. It has modules to manage blogs, lead generation, social monitoring, ads, and email marketing.
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2. Sisense
Our score: 9.7 User satisfaction: 99%A leading and award-winning software for preparing, analyzing, visualizing, and organizing data for your business. Sisense brings innovative and intelligent technology designed to address inquiries directly through a single channel, as well as gather and present your data as relevant insights that you can share using interactive dashboards.
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3. MailerLite
Our score: 9.0 User satisfaction: 89%An automated email marketing platform with powerful features for optimizing email campaigns. Using MailerLite, marketers can create dynamic, engaging email campaigns and set up workflows for automated email delivery. Built-in reports also provide data-backed insights into campaign results and metrics such as unsubscriber count and bounce rate. All these features come in an intuitive, visual interface for hassle-free use and onboarding.
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4. Zoho Analytics
Our score: 8.7 User satisfaction: 99%A powerful business intelligence, data analytics, and online reporting tool for creating data visualizations and generating actionable business insights. Zoho Analytics' self-service approach streamlines the data analytics process in a way that can be handled by anyone regardless of their technical skills.
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5. Pyramid Analytics
Our score: 8.6 User satisfaction: 97%Self-service analytics and BI platform for carrying out high-end analytics without relying on IT, works with both cloud and on-premise systems.
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6. Unbounce
Our score: 9.1 User satisfaction: 94%A cloud-based platform designed to streamline the landing page building process. Equipped with powerful features for landing page creation and optimization, Unbounce aims to increase your conversion rate. Moreover, Unbounce is equipped with AI-powered tools to further enhance your audience’s online experience, encourage engagement, and drive your sales.
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7. SE Ranking
Our score: 9.6 User satisfaction: 94%A cloud-based marketing platform for SEO and marketing professionals, SE Ranking comes with tools for SEO auditing, advanced keyword analysis, keyword grouping, competitor analysis, website ranking, and others. For SEO newbies, SE Ranking also offers comprehensive checklists, SEO guides, and best practices.
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8. IBM Business Analytics
Our score: 9.9 User satisfaction: 97%An integrated suite of business analytics tools that help drive organizational growth.
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9. Apache Hadoop
Our score: 9.8 User satisfaction: 99%A reliable, scalable, and open source software library and distributed computing framework developed for research and production-related activities; permitting users to process large amounts of data sets for data analysis, execute distributed parallel computing operations and tasks across clusters of servers and machines, and ensure the high performance and availability of applications that are running in Hadoop clusters.
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10. Looker
Our score: 9.6 User satisfaction: 95%Looker is a data-discovery platform that provides companies real-time access to relevant data to help them make better business decisions. A browser-based application, Looker can analyze any size of data for businesses of all sizes. It also has a user-friendly interface that even inexperienced data analysts can navigate with ease.
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11. Periscope Data
Our score: 9.5 User satisfaction: 98%Periscope Data by Sisense is an advanced analytics platform where businesses can securely conduct data processing, testing, performing queries, and others. Among Periscope Data's robust features include efficient query management, data preparation, data connection and analysis, custom data visualization, multiple sharing options, data and user management, and more.
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12. Board
Our score: 9.0 User satisfaction: 100%Board is an all-in-one business intelligence platform that combines business intelligence with performance management and data analytics. It comes both as a web-based and an on-premise platform and allows you to manage your workflows. With the software's predictive analytics, you can create plans and make adjustments to your business model and initiatives.
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13. EngageBay
Our score: 8.9 User satisfaction: 100%EngageBay is an all-in-one marketing, sales, and CRM platform designed to be an affordable alternative to expensive solutions. Considered as a true alternative to more expensive business solutions, EngageBay automates key business processes and routines to free you up to create meaningful customer experiences.
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14. Google Analytics
Our score: 8.7 User satisfaction: 99%Google Analytics is a software tool that summarizes data on high-level dashboards enabling you to generate various types of reports.
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15. Ortto
Our score: 8.7 User satisfaction: 97%Designed to collect customer data into a single platform to provide a complete view of each customer. This unified data also makes it easier for marketers to create dynamic audience segments and hyper-personalized marketing messages. Pre-made and customized marketing reports and dashboards also allow teams to accurately track campaign performance.
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16. Pecan
Our score: 8.5 User satisfaction: 97%A predictive analytics app that helps businesses solve critical problems and make smarter and data-driven business decisions.
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17. WebFOCUS
Our score: 8.2 User satisfaction: 100%Flexible, pervasive BI and analytics platform, able to deliver a broad range of governed analytical tools, applications, reporting, and documents to all business stakeholders.
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18. Zepto
Our score: 8.0 User satisfaction: 94%World's Simplest AI Powered Data Analytics Tool via the cloud. It provides AI-powered data analytics tool for everyone.
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Table of contents
Industry Report - Data Analytics Software for 2022
CloudRank™ system is a unique algorithm that our research team uses to evaluate Data Analytics Software solutions in a detailed and accurate way. The Winter 2022 edition of the ranking was prepared by Jenny Chang, our leading expert in the field of Data Analytics Software, who has authored 1380+ product reviews in this category. The goal of CloudRank™ is to present an unbiased, multi-layered perspective on Data Analytics Software, considering a wide range of metrics and factors, and educating potential customers about both opportunities and challenges associated with each piece of software.
In order to achieve full objectivity the position in our CloudRank™ is based on:
- Expert Score: which involves extensive analysis by our internal team which carefully examined all key elements of each software and testing it in real-life situations
- User Score: which involves an aggregated opinion of actual users of each product whose identity was properly verified
- Market Position: which involves general recognition of a given vendor on the market and reflects its overall popularity and reach
What do the tiers in CloudRank™ mean?
We’ve calculated a score for each product based on the average experience shared by our users in their product reviews and arranged the list in three tiers. You can see the methodology below on how the calculations were made.
- Leaders: those with a User Score of 8.5 or higher; this tier includes products that are currently leaders on the market and are appreciated by both experts and actual users. They always represent the best of what the Data Analytics Software market has to offer and are all worth trying out if you’re looking for a reliable solution.
- Contenders: those with a User Score between 8 and 8.5; this tier includes high-quality products that still have some minor drawbacks that prevent them from becoming leaders on the market. They always represent well-designed tools that, over time, will most likely develop into market leaders as the missing features are added.
- Rising Stars: those with a User Score between 7 and 8; this tier includes products that have high-potential but still lack some crucial features or services expected from a leading solution. They are products with solid foundations and a vision that makes us eager to see what they will become as their solution improves in the future.
Regardless of their tier, all products included in our CloudRank™ are popular, quality products considered top-performers by our team of experts. Make sure you read a more detailed review of each solution to find one that will work best for your specific needs and budget.
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MARKET POSITION
A score between 1 and 10 based on popularity and market reach of each product.
TOTAL score
A score between 1 and 10 based on the average of our Expert Score and User Score.
How does CloudRank™ work?
Market Position
A score between 1 and 10 based on popularity and market reach of each product.
Total Score
A score between 1 and 10 based on the average of our Expert Score and User Score.
CloudRank™ tier
Based on product's total score.
Rising Star
Contender
Front Runners
25 Most Popular Data Analytics Software
Here is a list of all 25 Data Analytics Software solutions evaluated with our CloudRank™ analysis. We have compared their features, user satisfaction, market presence and other key factors in an in-depth analysis you can find below:
Our score and features analysis:
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CloudRank™
Score:8.72
Score:8.72
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2. Google Analytics
8.67
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Score:8.67
Score:8.67
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CloudRank™
Score:8.66
Score:8.66
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}
CloudRank™
Score:8.65
Score:8.65
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100+
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}
CloudRank™
Score:8.64
Score:8.64
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100+
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}
CloudRank™
Score:8.54
Score:8.54
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100+
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7. Microsoft Power BI
8.49
Our score and features analysis:
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CloudRank™
Score:8.49
Score:8.49
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8. Qualtrics Research Core
8.49
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CloudRank™
Score:8.49
Score:8.49
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9. Salesforce Analytics Cloud
8.48
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CloudRank™
Score:8.48
Score:8.48
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10. Zoho Analytics
8.44
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Score:8.44
Score:8.44
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CloudRank™
Score:8.43
Score:8.43
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100+
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Our score and features analysis:
}
CloudRank™
Score:8.25
Score:8.25
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Our score and features analysis:
}
CloudRank™
Score:8.25
Score:8.25
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14. MicroStrategy
8.24
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CloudRank™
Score:8.24
Score:8.24
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CloudRank™
Score:8.23
Score:8.23
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16. AgencyAnalytics
8.16
Our score and features analysis:
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CloudRank™
Score:8.16
Score:8.16
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17. SAP BusnessObjects Lumira
8.12
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CloudRank™
Score:8.12
Score:8.12
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18. TIBCO Spotfire
7.92
Our score and features analysis:
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CloudRank™
Score:7.92
Score:7.92
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Our score and features analysis:
}
CloudRank™
Score:7.89
Score:7.89
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20. Sisense for Cloud Data Teams
7.85
Our score and features analysis:
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CloudRank™
Score:7.85
Score:7.85
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21. Oracle Analytics
7.66
Our score and features analysis:
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CloudRank™
Score:7.66
Score:7.66
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CloudRank™
Score:7.59
Score:7.59
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23. Amazon QuickSight
7.58
Our score and features analysis:
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CloudRank™
Score:7.58
Score:7.58
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Our score and features analysis:
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CloudRank™
Score:7.34
Score:7.34
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Our score and features analysis:
}
CloudRank™
Score:7.03
Score:7.03
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Best features
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Our report covered 25 most popular products from the Data Analytics Software category. We’ve analyzed their features, performance, integration, customer support, pricing, and several other key buying factors and combined it with feedback from user reviews to come up with the current list of best solutions:
- 2022 Data Analytics Software Leaders: Klipfolio, Google Analytics, Semrush, IBM Cognos, Sisense, Looker
- 2022 Data Analytics Software Contenders: Microsoft Power BI, Qualtrics Research Core, Salesforce Analytics Cloud, Zoho Analytics, Domo, Qlik Sense, Tableau, MicroStrategy, MATLAB, AgencyAnalytics, SAP BusnessObjects Lumira, Sisense for Cloud Data Teams
- 2022 Data Analytics Software Rising Stars: TIBCO Spotfire, Birst, Oracle Analytics, Alteryx, Amazon QuickSight, QlikView, BigID
Klipfolio managed to best 24 other competitors for the top spot in this year’s data analytics software CloudRank. Formerly known as Serence, the company initially focused on the consumer market and later moved into the dashboard and business intelligence space. Today, Klipfolio is one of the world’s leading data analytics software in the market.
This software is a cloud-based platform that allows businesses to build real-time dashboards that visualize critical data, automate data retrieval, and then manipulate it. It has a simple, intuitive interface engineered to aid its users and their organizations acquire real-time data from over 500 data sources which include web-based services such as Google Analytics, social media platforms like Moz and Twitter, on-premise data warehouses. This allows its users to make the most intelligent business decisions, take the best course of action, and drive their businesses towards success.
By seamlessly integrating with a wide array of data sources, Klipfolio can easily access mountains of information and automatically integrate and analyze it. This allows its users to focus on making better business decisions based on reliable and accurate data. As such, it comes to no surprise that more than 8,000 businesses trust Klipfolio to help them in their journey to grow their brands.
Most users of Data Analytics Software solutions confirm that in most cases these tools allow them to reach the following business goals:
- It analyzes customers’ browsing habits and previous purchases to predict their future requirements. [ 86.2% of users ]
- It assists us to find solutions to common issues. [ 85.6% of users ]
- It enables us to generate customized reports. [ 85.0% of users ]
- It helps us conduct interactive sessions with business users. [ 86.6% of users ]
- It provides insights based on up-to-date info. [ 86.4% of users ]
How did we select products for this Data Analytics Software report?
The Winter 2022 version of the report includes a total of 25 Data Analytics Software products that were compared and analyzed by our team. We selected them based on the following factors:
- Popularity of a given brand in the SaaS market (based on our own market research)
- How popular a given brand is among FinancesOnline users (based on number of mothly readers for each review page)
- Availability of statistical data generated from user reviews of a particular product (we excluded products with not enough data to draw meaningful conclusions)
- The current listing reflects the state of our database and research as of February 2022. An updated version of the report will be released quarterly to keep data fresh and incorporate information about shifts and changing trends in the market.
What are the current Data Analytics Software trends?
Businesses to take advantage of data analytics and IoT Integration
The estimated number of IoT connected devices by 2025 is 75.44 billion worldwide. As you can imagine, all these devices are producing data that businesses can use to gain a better understanding of their operations, develop new products and services, and provide a more personalized customer experience.
In order to extract actionable insights from the large volume of data produced by the IoT, data analytics must take place. This will increase the reliance of businesses on data analytics software and other business intelligence tools that can make it easier to organize and make sense of the data they receive from various sources.
Source: Statista
Natural Language Processing (NLP) features will continue to increase in BI software
NLP capabilities help organizations better understand the context of their data. For example, it can help identify patterns in text search, understand social media sentiment, and make document review more efficient. It’s the technology that makes it possible for us to “talk to machines,” so when you need to know how your business revenue has changed in the last quarter, you simply ask the question. This is the same technology used in AI assistants like Siri and Alexa.
Several BI software in our top 25 already integrate NLP in their features. Sisense and Tableau, for instance, can narrate data visualization with text. As a result, the subjective interpretation of graphs or charts can be avoided.
Currently, NLP is not perfect; however, we can expect that the technology will improve and more BI and analytics vendors will include it in their product. Doing so will not only enhance user experience when performing queries but also make their product easier to use.
Improved efficiency and productivity Faster, more effective decision making Better financial performance Identification & creation of new product & service revenue Source: Statista
Global Survey: Benefits of the Use of Data & Analytics
Global Survey: Benefits of the Use of Data & Analytics
Improved efficiency and productivity: 64
Global Survey: Benefits of the Use of Data & Analytics
Faster, more effective decision making: 56
Global Survey: Benefits of the Use of Data & Analytics
Better financial performance: 51
Global Survey: Benefits of the Use of Data & Analytics
Identification & creation of new product & service revenue: 46
More businesses will utilize graph analytics
Graph analytics, also called graph database, makes complex relationships between data simpler to understand via visual structures made up of lines and dots. Marketing managers, for example, use graphs when performing social network analysis. By studying a visualized representation of their data, they can identify strong influencers to work with in triggering interest and reactions for specific campaigns.
Aside from marketing, graphs analytics can also be useful in spotting fraud or detecting money laundering activities. For instance, large transactions between bank accounts can be spotted and flagged by authorities.
In other industries, graphs analytics can streamline processes in manufacturing and optimize routes in the aviation industry. Governments and scientists have also been using the approach to fight the COVID-19 pandemic. Graphs can be used to determine cases and perform contact tracing.
With a wide range of applications and benefits, it’s not surprising to know that graph analysis is expected to experience 100% growth until 2022. This makes us certain that BI software vendors will continue to enhance the data visualization capabilities of their products.
Data analytics software is used by organizations and companies to get useful insight from the business data they collect. There are scores of quality programs in this niche. So, how do you do informed comparisons to select the best data analytics software for your needs? We make your task simpler by detailing the key factors and features that you should look for in data analytics tools.
Get to know each product with free trial
Start your search for the best data analysis software by registering for the free trial or demo of top tools. Popular data analysis software providers present this facility to help you try out their solution’s main features free of cost. You can also utilize the opportunity to do a detailed comparison with other apps. We recommend you check out Google Analytics, IBM Cognos, MATLAB, Tableau, and Minitab. These products have been given high ratings and rankings in our data analysis software reviews.
Targeted Businesses
Small, medium-sized, and large companies, as well as multinational organizations and global enterprises, can utilize data analytics software to make the most of the business data they collect.
Examples of Data Analytics Software
- Google Analytics: A popular web analytics service utilized by thousands of enterprises worldwide. It offers a range of premium analytics features for both mobile and traditional users. The tool summarizes data on clear dashboards from where you can generate different kinds of reports. Individuals and small businesses can utilize the lifetime free package, while larger companies can opt for a paid plan for their greater needs.
- IBM Cognos: Offers a set of intelligent self-service features that enable you to make fast decisions based on insight. The best part is you can make or configure reports and dashboards on your own. The interactive and formatted dashboards boast custom visualizations, and scalable scheduling and distribution capabilities. Plus, you get a wide range of analytics tools such as analytical reporting, trend analysis, advanced analysis, and what-if analysis.
- MATLAB: A simulation, modeling, and programming solution. This Computer-Aided Engineering (CAE) system helps you to analyze data, build algorithms, and develop models. Its professionally designed tools have passed complete documentation and rigorous testing. Interactive apps show how different algorithms work with users’ data. In addition, the software is scalable and you can run analyses on clouds, GPUs, and clusters with minimal code alterations.
- Tableau: A business intelligence solution that enables organizations to visualize and comprehend their data. With this tool, you can quickly link, visualize, and share data seamlessly on all devices from the PC to the iPad. In addition, you don’t need coding skills to create and publish dashboards that can be shared with customers, colleagues, or partners. Tableau Desktop is a self-service analysis tool that helps you view data and answer queries quickly. Tableau Server assists you to publish dashboards from your Tableau Desktop on any mobile device or web browser.
- Minitab: A provider of statistics education and quality improvement software. Their main product, Minitab Statistical Software, is utilized by organizations to analyze and graph their business data. Besides, numerous universities and colleges also use this program. The Statistical Software works more effectively with the other solutions in the Minitab suite. These are Minitab Companion which offers a range of features to help companies attain product and process excellence, and Minitab Quality Trainer which assists users to master statistics.
Types of Data Analytics Software
data analytics tools can be used to perform 4 main types of analytics:
- Descriptive analytics. Tells you what happened. For example, retailers can learn the average weekly sales volume.
- Diagnostic analytics. Drills down to find dependencies and identify patterns. Companies can get deep insight into a specific issue.
- Predictive analytics. Forecasts what’s likely to happen. It uses the results of descriptive and diagnostics analytics to predict future trends.
- Prescriptive analytics. Prescribes the action needed to capitalize on a promising trend or eliminate a future issue. For example, companies can find opportunities for repeat purchases based on sales history and consumer analytics.
Key Features of Data Analytics Software
- Text and semantic analytics. Scrutinizes large volumes of text to identify sentiment, relationships, and patterns. This feature is applied to emailed communications, live chat conversations, and comments on social media.
- Predictive analytics. Makes forecasts about future opportunities and risks. For instance, predictive analytics can be utilized to test the impact of marketing campaigns based on the results of previous campaigns.
- Online analytical processing (OLAP). Studies multidimensional data from a number of perspectives. It comprises of three operations: data consolidation, data classification or sorting (drill-down), and data analysis from a specific perspective (slice-and-dice).
- Querying. A query is the question asked to a database. Answers are returned by the analytics solution in the form of data patterns and presented as reports.
- Managed Query Environment (MQE). This feature helps administrators set role-based limitations on the kind of queries users can submit, the type of databases the queries can access, and the kind of reports they’ll generate.
- Reporting. The results obtained from a database query are termed reports. They can be in different sizes and shapes based on the available data, the software utilized, and the particular nature of the query.
Benefits of Data Analytics Software
- Interactive sessions. Cloud-hosted data analytics software help you to analyze data effectively and get instant results. On top of that, you can invite your team members to take part in interactive sessions and give them access to the insights they require.
- Customized reports. You can easily generate relevant and comprehensive reports on key trends, patterns, and metrics. Pick the data you want included in a specific report and the software will generate it quickly using the latest available info.
- Anytime, anywhere access. Cloud-based solutions can be accessed from anywhere, on any internet-ready device. This allows you to login from anywhere, anytime to get quick answers and insights.
- Up-to-date info. Dated info is no good for making important decisions. Data analytics provides relevant and fully up-to-date info and insights based on current data.
- Other benefits. You can find the link between your new marketing campaigns and enhanced sales. Analyze customers’ browsing habits and past purchases to predict their future needs. Finally, data analytics software helps you to boost internal workflows and find solutions to common issues.
Latest Trends
Data governance. The European Union’s General Data Protection Regulation (GDPR) and other data regulations have made data governance important of late. Apart from regulatory compliance, another driver is data catalogs which make data sets in a data lake more organized and discoverable. Data discovery solutions help to make your data lake more usable. Thus, data discovery tools and data catalogs are further expected to drive the governance wave.
Cloud data lock-in. Data lakes based on cloud storage are being widely adopted. In fact, data lakes are an important selling strategy of top cloud vendors. Companies that store their data in a particular cloud solution are likely to do their analytics work on the same platform. This includes data preparation, predictive modeling, analytics, and model training. Thus, the winning cloud vendor is likely to get more business as they will lock in their clients.
Potential Issues
Technical issues. In a survey by SearchBusinessAnalytics.com, businesses named implementing analytics technology, consolidating these technologies, and managing multiple analytics tools as the top challenges they face in deploying analytics software.
Effective use of analytics. The above survey also found that effective use of analytics is another main challenge faced by companies. Other concerns are expanding the use of analytics technology to more users, and getting executive support and funding for analytics projects. Industry experts state that to successfully deploy analytics tools, companies need to focus on improving collaboration with business users and ensure they are able to efficiently utilize the new technology.
List of Data Analytics Software Companies
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Things to consider when you invest in a SaaS
The first and most important thing is to ensure the app is perfect for your organization’s requirements. Do not worry about the delivery method and pricing model and focus on getting the right program. Second, you should invest some time to do proper research on the background of the provider and the features of the product. Otherwise, you may end up paying a high price if the platform proves to be a bad fit.
Another important thing is you should always peruse the contract and understand the terms and conditions. SaaS contracts are known for clever phrasing, so be sure you know what you are getting into. Do not get chumped into an evergreen contract. Be certain about the renewal terms as well as the notice time needed to cancel the renewal.
You will be surprised to learn the gains you can earn by negotiating intelligently. SaaS software is a competitive market and providers will be willing to offer you a price reduction to earn your business and continue it. Make use of this opportunity to save some money.
Realize that the teaser rate is presented only for a short period. Learn about the total cost you need to shell out after the initial discount ends. Also, compute the long-term fee to know what you are getting into.
Frequently asked questions about Data Analytics Software
What is the best data analytics software?
The best data analytics software is Sisense. Sisense is a business intelligence platform that offers a comprehensive set of features that simplify data collection and analysis, making it easier for users to make data-driven business decisions. The platform is flexible, too, making it the ideal data analytics solution for businesses of all sizes.
With Sisense, users can easily combine data from multiple sources to gain valuable insights from a single source of truth. Built-in connectors for tools such as Excel, Google Adwords, and Zendesk ensure that joining different data sources takes just a few clicks. This ease of use ensures that users can spend less time on scripts and code and focus on analyzing data. These seamless integrations also improve accuracy even for large data sets.
Sisense is also designed for quick deployment and onboarding. Users can build interactive dashboards and reports through drag-and-drop functions. The system also comes with built-in data visualizations to help users discover insights more quickly. In addition to these features, Sisense provides AI-assisted exploration and automatic analysis to make data and insights more accessible to users.
What are the benefits of data analytics software?
Valuable business insights. Through data analytics software, users can discover valuable insights in the data they collect and use these insights to make more informed data-driven business decisions.
Advanced data analysis. Data analytics software can easily collect, process, and analyze large volumes of data. These platforms often come with features for forecasting and identifying trends in data as well.
No information silos. With data analytics platforms, data and insights are accessible to all users in the organization. The platform’s ability to combine multiple data sources also improves the accessibility of data.
Data accuracy. Data analytics systems can ensure that users work only from clean, organized datasets, and these tools’ built-in integrations for third-party tools help prevent errors caused by manual input.
Improved productivity and efficiency. Through these tools, users can spend less time tracking down data and instead focus on analyzing data. As a result, users can take advantage of data insights to improve their organization’s efficiency.
What are the features of data analytics software?
Dashboards and data visualization. Most data analytics software can visualize data and put graphs and charts on dashboards for easier tracking. These dashboards are also customizable so users can track key metrics for their organization.
Custom reports. Many of these solutions come with templates to help users quickly generate generic reports. Users can also create customized reports to drill down into more detailed data levels and take full advantage of available data.
Mobile access. Data analytics software also provide mobile access, so users can access data whenever needed. Some platforms offer web-based dashboards for this purpose, while others come with their own mobile app.
Integrations. The best data analytics software come with built-in connectors and integrations to ensure compatibility with third-party systems like CRM software and sales tools. These integrations can help users save time and effort in integrating multiple data sources.
Security and access management. Data analytics tools allow business owners and managers to set various user roles and access levels to ensure that only authorized users can access important business data. Other security features of data analytics software include SSO and data encryption.
What is the easiest data analytics software to use?
Data analytics solutions that are easy to use ensure faster deployment and adoption. The following tools are popular for their intuitive interface:
Salesforce Analytics Cloud. Salesforce Analytics Cloud is powered by Einstein Analytics and Tableau, both of which make it easier for users to visualize data and discover valuable insights. Users can use guided data exploration to query data and analyze data sets.
Looker. Looker ensures that data is easily accessible through built-in integrations with tools such as Google Drive and Dropbox. The platform also makes it easy for users to design their own data visualizations.
Reveal. Reveal is built on flexible architecture, so users can quickly embed data from the software into existing applications and tools. Dashboards are also responsive to enable real-time monitoring of KPIs.
What is a good free data analytics software?
Contrary to popular belief, data analytics software won’t necessarily burn a hole in your wallet. The following data analytics platforms have free plans available:
Qualtrics Research Core. Free users of the platform can build surveys with unlimited questions and up to eight question types. The Free plan also includes survey logic and randomization features, as well as summary reports and online reporting.
Zoho Analytics. The platform’s Free plan includes use by 2 users, as well as unlimited dashboards and reports. Users can also access up to 3 query tables and 5 workspaces and use the platform’s mobile app.
Google Analytics. One of the most popular data analytics platforms today, Google Analytics is a freemium web service that allows users to monitor a single website or mobile app through tracking codes, which collect data from site visitors.
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