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Hackernoon logo7 Data Analytics Tools to Boost Your Business  by@joey

7 Data Analytics Tools to Boost Your Business 

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@joeyJoey Bertschler

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The power of data analytics guides our modern world in virtually all fields: entertainment, financial technologies, healthcare, manufacturing industries, and more.

Expert data analysts process petabytes of data to get valuable insights, but not every business owner has the time or resources to apply complex data analytics to their organization's data. 

However, it doesn’t take a computer science degree to make the most of data analytics that can make your organization grow. Check out this list of the best tools to get positive results for your organisation—no programming skills needed.

Why bother analyzing data? 

More than ever, businesses and financial institutions produce enormous amounts of data. Sales and market research, employee statistics, accounting information, website and social media traffic—all of this information is considered valuable data that businesses can use to profoundly grow their operations and strategically structure their workplaces. 

Integrating data solutions into business positively affects organizations in many ways—using trend data to direct best practices, guiding decision-making with quantized evidence, identifying target audiences, and ensuring optimal marketing campaigns. 

But before this data can be understood by top management and other decision-makers in a company, it needs to be processed, cleaned and analyzed to uncover actionable insights. Analyzing internal data helps uncover hidden patterns, correlations, anomalies and other surprising details that have the potential to boost business practices—and you don’t even have to hire a Data Analyst to get these benefits. 

Below are seven user-friendly tools that can help business owners gain actionable insights from their data.

Rattle GUI 

Rattle is an open-source data analytics software built with non-technical users in mind. With a remarkably simple point-and-click user interface, it has gained its popularity in the market for data mining using R.

Rattle can deliver powerful statistical features which aid businesses in correlating sales efforts with marketing campaigns, analyzing customer feedback and even basic market trend predictions.

Another handy feature of Rattle is that it can generate code based on your analysis. This feature is incredibly useful if you decide to outsource your heavy-duty data analysis, but before that stage you can get a lot of information from playing around with this easy interface.

Rapid Miner 

RapidMiner has been a leader in the advanced analytics field since Gartner named them in their Magic Quadrant for Advanced Analytics in 2016. This tool not only helps businesses build machine learning models that predict trends, but also is capable of building product recommendation tools for their users.

RapidMiner has a great impact on conventional data analysis done across several industries at companies around the world. It has impacted businesses positively; one such example is Master Loyalty Group. Thanks to its ease of use and interactive GUI, Master Loyalty Group was able to build a recommender tool which pushes only the relevant products that a customer might be interested in on the customer's feed.  

If you’re a business owner and don’t know code, RapidMiner could be a helpful tool for you.

Weka

Weka is an intuitive and easy-to-learn software that was built using Java. It is also popular for its presence in the academic world where it’s widely used to teach machine learning to beginners. 

Popularly used to create classification algorithms for small business owners, it is extremely useful to understand a company’s user base better. Classification algorithms can be constructively used to segregate the user base of a product-based business. It can classify customers into categories as regular customers, not so regular customers and first-time customers. 

So if you want to understand your customer base using data from marketing and sales, Weka would be a great option to get started.

Tableau

Tableau is one of the most popular platforms when it comes to data visualization. It gains its popularity within businesses from its user experience and its fast processing speed. 

Apart from working with a fairly large amount of data, Tableau is also able to integrate live data from the market. This is a huge advantage as it keeps the data and the businesses updated on the current trends in the market. Visualizing multiple graphs through Tableau aids businesses to take decisions quickly and saves a lot of development time.

Tableau doesn’t necessarily require laptops to work on. Its responsive software aids the user to operate on smartphones and tablets too. This is a huge advantage when the users are early-stage entrepreneurs who need to travel a lot.

Datawrapper

If your organisation is confident of not needing a powerful analyzing tool, Datawrapper is your catch as it’s fast and can visualize data using line charts, bar charts, columns, stacked bar charts, maps, etc. 

As a basic visualization tool, it’s often used for lighter models and especially for BI (business intelligence) applications. BI enables business owners to make quick decisions based on analytical evidence, which helps the organisation generate better revenue and sometimes becomes a deciding factor for marketing campaigns. 

The feature that makes Datawrapper a standout is that, as a web app, it doesn’t require any software installation. Once you have the data in CSV format, you just need to paste the file on the online tool and Datawrapper will create a bar chart, line graph or any other related effective graphic visualization of the data. This is great for quick visualizations, and they look pretty too!

Trifacta 

If you are a business owner who wants to analyze big datasets, for example consumer demographics, then you will need to process the data through different visualization techniques. With Trifacta, you can do this easily in just a few clicks.

Businesses and firms are increasingly using BI to make accurate decisions such as deciding efficient PR campaigns, analyzing which product is performing better and sometimes becoming a key factor for future collaborations. 

Before sending the data to different analytical tools, it is necessary to clean the raw data; This is where Trifacta steps in and fabricates the wrangling processes to be faster and easy to operate for business owners who come from a non-technical background.

It is trusted by businesses because of its intelligent nature which recommends algorithms on its own, hence yielding more results from the data.

Excel

Last but not least, Excel is one of the oldest data science tools that has aged like a fine wine. Even after countless years, a large number of problems faced in analytics projects are solved using this software. With community support, tutorials, free resources, excelling in this tool has become quite easier. 

The data visualization features in Excel make intuitive data analysis so much simpler for businesses, and it can also be easily adapted to several verticals from understanding marketing campaigns effectiveness to forecasting consumer trends.

Apart from Excel’s data analysis applications, it has a wide range of applications in various teams. Excel is used in financial planning of corporates employing various formulas and it is also used in human resource planning and marketing management.

Once you start working on these tools of your choice, you’ll soon realize that knowing programming for predictive modelling isn’t a necessity. You can accomplish the same results with these tools and, in some cases produce results that rival outsourcing your data analysis.

Once your organisation starts adapting these tools for analytical purposes, there is potential to observe considerable growth in the revenue of the organisation.

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