{"id":9983,"date":"2021-10-01T13:44:40","date_gmt":"2021-10-01T11:44:40","guid":{"rendered":"https:\/\/careerfoundry.inbearbeitung.de\/en\/?p=9983"},"modified":"2023-12-19T15:23:16","modified_gmt":"2023-12-19T14:23:16","slug":"data-analysis-software-tools","status":"publish","type":"post","link":"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/data-analysis-software-tools\/","title":{"rendered":"The 7 Top Data Analysis Software Tools"},"content":{"rendered":"

Data analytics. Once the preserve of highly-trained data specialists alone, over the past few years it’s spread to all industries and aspects of business.<\/strong> <\/span><\/p>\n

With an increasing number of digital professionals requiring easy access to data\u2014and the ability to manipulate it\u2014there has been a boom in data analysis software. The business intelligence market is pretty competitive though, and it\u2019s rapidly changing, which makes it hard to keep track of which tools might be right for you.<\/span><\/p>\n

In this post, we look at the current most popular data analysis software tools on the market. While the tools you use will depend on the task at hand, we\u2019ve selected those<\/span> shortlisted by Capterra<\/span><\/a>, a renowned marketplace vendor and subsidiary of the respected global research and advisory firm,<\/span> Gartner<\/span><\/a>.<\/span><\/p>\n

Without further ado, here\u2019s our list of the seven top data analysis software tools. Topping our list is\u2026<\/span><\/p>\n

1. Holistics<\/span><\/a><\/h2>\n

Pricing:<\/b> Starts from $150 a month. Free trial available.<\/span><\/p>\n

Deployment:<\/b> Cloud, SaaS, web-based.<\/span><\/p>\n

Founded in 2015, Holistics is a relative newcomer to the data analytics software market. They are a modern, self-service business intelligence platform that allows users to answer data questions without input from technical teams\u2014and this non-technical focus is their unique selling point. The software covers everything from data prep to integrated reporting, visual dashboards, and ETL (extract, transform, load) tools, as well as a variety of data connectors and data discovery features.<\/span><\/p>\n

As a fairly new tool, Holistics\u2019 support features are a little limited, but they can provide training in-person, or live online, should you need it. They also have plenty of documentation to call on. However, such is the ease of their drag-and-drop reporting and visual metrics that most find the platform pretty intuitive to use. <\/span><\/p>\n

The software is not without its teething problems, though: the user interface can be a little inconsistent, while some important features are currently limited or missing entirely. However, the team behind the tool is enthusiastic, and clearly willing to help where they can. They are working to create a great piece of data analytics software that can cater to all non-technical users.<\/span><\/p>\n

2. Microsoft Power BI<\/span><\/a><\/h2>\n

Pricing: <\/b>Starts from $10 per feature, per month. Free trial available.<\/span><\/p>\n

Deployment: <\/b>Cloud or desktop.<\/span><\/p>\n

Microsoft Power BI tops a lot of “best of” lists. There\u2019s a reason why, though, and it\u2019s not entirely because it\u2019s created by one of the richest tech companies in the world! Power BI has evolved from years of Microsoft\u2019s experience in the computing and data spheres. <\/span><\/p>\n

Officially launching in 2013, it’s fast become a ubiquitous piece of data analysis software used by organizations the world over. Popular with developers, analysts, and IT users alike, as well as non-technical personnel, its features include a range of great visualizations, customizable dashboards, and connectivity to over 70 different on-premise and cloud data sources. Power BI also boasts natural language search\u2014something that\u2019s increasingly needed in data analytics as more and more organizations try to decipher the nuance of the written word.<\/span><\/p>\n

As a tool designed for both technical and non-technical personnel, Power BI lets users visualize data, breaking it down to a level that\u2019s easy to interpret and understand, even for novice analysts. It’s also benefitting from Microsoft’s cooperation with OpenAI, offering AI-enhanced capabilities to develop reports quickly for users.<\/span><\/p>\n

It does suffer from a few of the issues that seem to plague many Microsoft products, though. For instance, its user interface is a bit clunky and its proprietary programming language, DAX, is not all that easy to pick up. <\/span><\/p>\n

These issues aside, though, Power BI is a generally useful tool that\u2019s well worth adding to your analytics toolkit.<\/span><\/p>\n

3. Mode<\/span><\/a><\/h2>\n

Pricing: <\/b>Available on request but has a free version. Free trial available.<\/span><\/p>\n

Deployment: <\/b>Cloud-based only.<\/span>\u00a0<\/span><\/p>\n

Data analysts who need to juggle applications and modules coded in different languages should look no further than Mode. <\/span><\/p>\n

A data science platform integrated with powerful business intelligence tools, those with programming expertise will be pleased to find that Mode supports SQL, Python, and R. As a result, teams using the platform can each use the language they\u2019re most familiar with. Mode also has a great range of user support options, which include a help desk, online chat, a detailed knowledge base, as well as all sorts of training and tutorials (such as SQL for beginners) via its webinars or live workshops.<\/span><\/p>\n

Mode\u2019s interactive visualizations add real data visualization flair. These are available out of the box, but can also be customized using HTML, CSS, and D3.js (for those who have a bit more programming expertise). While it lacks some of the functionality of more well-established business intelligence platforms, Mode\u2019s internal team is agile and open to improvements. Combined with their support for all the common data analytics programming languages, their willingness to add new features adds up to a winning formula.<\/span><\/p>\n

4. Tableau<\/span><\/a><\/h2>\n

Pricing: <\/b>On request but starting at $15 per month for Viewer access. Free trial available.<\/span><\/p>\n

Deployment: <\/b>Cloud, desktop, on-premise, and mobile\u2014the whole package!<\/span><\/p>\n

If there\u2019s any tool on this list you\u2019ve already heard of, <\/span>it\u2019ll likely be Tableau<\/span><\/a>. One of the most ubiquitous pieces of data analytics software in the industry, Tableau is renowned for its ease of use and delectable visualizations. It\u2019s the go-to tool for representing complex data with excellent visuals and features an easy-to-use drag and drop interface. <\/span><\/p>\n

Having evolved from pure visualization into broader BI, Tableau was acquired by Salesforce in 2019. Being integrated with Salesforce\u2019s customer relationship management (CRM) system has secured Tableau\u2019s data viz market dominance, especially for marketing professionals. Its sleek design, integrated compliance tracking, and content management features\u2014to name a few\u2014mean it\u2019s suited to industries from retail to healthcare.<\/span><\/p>\n

What’s more, in 2023 the company added Tableau AI<\/a>, which offers users democratized data to simplify insights. As trust and AI ethics are a huge consideration<\/a> for all businesses, the company bases the feature on the Einstein Trust Layer, allowing data privacy and security to be respected.<\/p>\n

Like Mode, Tableau has plenty of available training options, although their after-sales support sometimes leaves a little to be desired. While visually appealing, it\u2019s not ideal for all data analytics tasks, either. For instance, it includes a handful of data prep and wrangling features, but isn\u2019t ideally suited to heavy data pre-processing. For that, you\u2019ll need to do a bit of work upfront, using a tool like Excel or Python. <\/span><\/p>\n

However, with the free version,<\/span> Tableau Public<\/span><\/a>, covering most of the core features and offering great community collaboration (allowing you to learn from other users) you can at least test-drive before you buy!<\/span><\/p>\n

5. Minitab<\/span><\/a><\/h2>\n

Pricing: <\/b>Starts from $1,851 per year for a single user. Free 30-day trial available.<\/span><\/p>\n

Deployment: <\/b>Cloud and desktop.<\/span><\/p>\n

Minitab is a powerful, well-established piece of statistical data analysis software. First released in 1974, universities and colleges around the world commonly use it in their statistics education programs. <\/span><\/p>\n

Naturally, Minitab has evolved a great deal since its inception. It’s now a robust platform with wide-ranging functionality. This includes the usual data analysis and querying functionality, as well as modern functions like artificial intelligence and machine learning tools, data blending, forecasting, and specialized statistical tools for the education and healthcare sectors.<\/span><\/p>\n

Being such an established player, Minitab has a huge number of statistical analysis features, allowing you to get into the granular detail of your data. While this is an obvious draw, it\u2019s also arguably one of Minitab\u2019s drawbacks\u2014the tool has so many features that it, too, has a pretty steep learning curve, and minimal tutorials to help, although you will <\/span>find some on YouTube<\/span><\/a>. In short, Minitab isn\u2019t the ideal tool for beginners and you\u2019ll need some foundational understanding of statistics before diving in. It\u2019s also a little pricey, reflecting its common use in educational settings. But if you\u2019re looking for something solid and wide-ranging, Minitab will have your back.<\/span><\/p>\n

6. Stata<\/span><\/a><\/h2>\n

Pricing: <\/b>Starting from $48 a year. Free trial available.<\/span><\/p>\n

Deployment: <\/b>Cloud, desktop, and on-premise.<\/span><\/p>\n

For data analysts working in more technical fields, Stata sits alongside Minitab as a piece of robust data analysis software for technical personnel. Designed specifically to support professional researchers in academic fields like economics, epidemiology, or political science, Stata is a heavy-hitting platform that\u2019s suitable for experienced data analytics professionals. At the same time, it aims to cater to those with fewer technical skills, such as managers who need to create and export custom reports using point-and-click functionality.<\/span><\/p>\n

For those who need them, Stata offers hundreds of statistical features, from regression tables to multivariate and predictive analytics, as well as mapping for a wide range of data models. You can also export to numerous formats. For those who get stuck, there\u2019s an array of literature to refer to as well, although its menu-driven approach makes it easy to use. On the downside, Stata can be a little slow sometimes, especially when dealing with larger datasets. For a programmer-friendly tool, it has a surprisingly limited number of customization options available and minor errors in code can skew your results quite heavily. Something to keep in mind! But for an all-round tool, it does the job it sets out to do.<\/span><\/p>\n

7. Grow<\/span><\/a><\/h2>\n

Pricing: <\/b>Available on request, but priced per feature. There’s also a free trial available.<\/span><\/p>\n

Deployment: <\/b>Cloud and mobile.<\/span><\/p>\n

Founded in 2014, Grow is another relative newcomer to the data analysis software market. As the last item on our list, its key selling point is that it’s a completely code-free platform. Offering sleek UX and UI design with drag-and-drop interfaces, Grow is suitable for all kinds of non-technical users. Fresh innovations are also regularly included. It\u2019s particularly useful for small businesses because it includes the full stack\u2014data warehousing, ETL tools, and business intelligence\u2014in a single solution.<\/span>\u00a0<\/b><\/p>\n

While non-coding platforms inevitably lose something in the way of feature customization, Grow minimizes this issue by regularly updating with new functionality. It promises excellent data connectivity, pulling raw data from a selection of different platforms commonly used by smaller businesses. <\/span><\/p>\n

It also offers a constantly expanding range of reporting functionality. While not suitable for detailed statistical analysis, that\u2019s not the market it’s designed for. If you need more bespoke functionality, be sure to check out one of the more codable tools on our list!<\/span><\/p>\n

Wrap up and further reading<\/span><\/h2>\n

So there we have it! Seven of the most popular data analysis software tools on the market right now.\u00a0<\/span><\/p>\n

As we\u2019ve seen, there\u2019s a huge diversity of data analytics platforms available, catering to everyone. These range from highly technical specialists with expertise in complex programming, to the average marketer or manager who simply needs to produce slick reports with minimal effort. <\/span><\/p>\n

What’s more, in 2023, most of these data analysis software tools were supercharged with the integration of generative AI<\/strong>. The leaps in large language models (LLMs) has meant that the analytical and organisational capabilities of these tools has increased. AI will be able to help you in the form of new smart functions, or even a copilot working alongside you to get the analytics you need, faster.<\/span><\/p>\n

Be sure to check out the rest of Capterra\u2019s <\/span>recommended tools<\/span><\/a> to see which other ones are popular right now.\u00a0<\/span><\/p>\n

To learn more about data analytics, check out this<\/span> free, 5-day data analytics short course<\/a><\/strong> or read the following posts for more introductory topics:<\/span><\/p>\n