Choosing the right statistical analysis tools

By Katrina Wakefield

We live in an increasingly data-orientated business and consumer world. On a day-to-day basis, massive amounts of data - structured, unstructured, complex, simple – is created and transferred throughout today’s digital landscape. And, as data is constantly being created and transferred, no one knows exactly how much of it exists. According to research by research group IDC (International Data Corporation), the world will be creating 163 zettabytes of data a year in 2025 – ten times the 16.1 ZB (zettabytes) of data generated in 2016.

This scale of data creation and transference has been facilitated by rapid advancements in technology; smartphones, IoT-enabled devices, the Internet and others – have all contributed to the growth of this data, resulting in diverse data sets that vary in size and complexity, more commonly known as ‘big data’.

From a business perspective, this wealth of data is a massive opportunity; but how can it be analysed? As data sets continue to grow in both size and complexity, traditional data processing and analytics software is quickly becoming redundant.

How can businesses analyse such complex and unstructured data to develop insights?

As data comes in varying sizes and structure, it is incredibly difficult to analyse with standard tools. To extract insights from these large, unstructured and complex data sets, businesses not only need sophisticated analytics and machine learning, but also statistical analysis tools to sift through the data and analyse it at scale, plus visual statistics software to visualise data and facilitate data interaction and exploration. The volume of data that exists today makes statistical analysis an incredibly powerful approach, but it’s vital that businesses acquire the right solutions.

What is statistical analysis?

Statistical analysis is a component of data analytics that is concerned with the scrutiny of data to identify underlying patterns and trends. Businesses across every industry and government departments around the world utilise statistical analysis tools to develop insights, conduct research and support planning.

What are statistical analysis tools?

Statistical analysis tools are designed to analyse, describe, summarise and compare data. These tools can be relatively simple packages, such as Excel, or more advanced analytics suites that utilise specialised software and algorithms to deliver more in-depth insight and create visual reports. In summary, statistical analysis tools enable businesses to scrutinise data of every scale and complexity – with granularity – to understand underlying trends and patterns and use this insight to refine business activities.

Choosing the right statistical analysis tool

What should businesses keep in mind when looking for a statistical analysis tool?

In order to choose the right solution(s), a business needs to first assess the quantity, quality, type and complexity of the data it manages – after all, utilising sophisticated statistical analysis for simple data sets is highly impractical. Statistical analysis tools really demonstrate their capability in environments with dense, complex and diverse data sets that cannot be analysed with a standard analytics solution. Typically, statistical analysis tools offer data visualisation to provide a clear view of data, proven statistical procedures to interrogate data, accurate data analytics, high-impact graphs to show results in the best form possible, web-based development environments and repeatable processes. Not every business will need all of these tools to assess its current data environment. Choosing the right statistical analysis tool – or tools – is highly dependent on what the business wants to achieve with its data. It’s also important to consider how these tools will integrate into business’ existing technology ecosystem and whether or not they can be supported.

What if a business needs more than just a statistical analysis tool?

While statistical analysis tools can help businesses to interrogate data and access deeper insights, these tools are – at the end of the day – just tools; individual solutions that may not integrate with the business’ overall technology ecosystem and therefore not deliver a “complete” view of its data. Furthermore, these tools may not provide the necessary enterprise-grade functions or high-performance analytics that large businesses, multinationals or businesses that process large volumes of data need.

What if a business wants a more flexible solution that can deliver analysis at every level of operations?

What if the business needs a specialised and enterprise-wide package?

To go further with data analysis at firm-wide level, businesses will need a suite of solutions, on top of their existing statistical analysis tools, to effectively capture, assess and manage growing data sets. Most standard analytics software packages and architectures just cannot keep up – they were not designed to handle iterative analytical development or diverse data environments.

As businesses start to approach the next stage of statistical analysis, they need a solution that is fast, large-scale, advanced, easily maintained, expandable, customisable and unified across the business. With this considered, the next step in the process is advanced statistical analysis software, such as SAS’ statistical analysis software.

Stop guessing and start knowing with SAS’ enterprise-grade statistical analysis software

With nearly four decades of experience developing statistical analysis software, SAS’ solutions can deliver the results businesses need. Unlike statistical analysis tools, SAS’ statistical analysis software is designed to provide specialised and enterprise-wide needs, utilising quality-tested algorithms, statistical modelling and machine-learning techniques to allow businesses to better understand their data and predict outcomes; all in a single environment.

It’s an all-in-one statistical analysis package that covers every area, including: analysis of variance, regression, categorical data analysis, multivariate analysis, psychometric analysis, cluster analysis, nonparametric analysis, mixed-model analysis, survey data analysis and much more. The software features an accelerated release schedule, keeping pace with the expanding field of statistics, ensuring businesses are using the latest statistical techniques and modelling tools to analyse data.

When combined with the cloud-based visual statistics suite SAS Viya, businesses have a statistical analysis package that provides the means to analyse data at scale, deliver fast results and create visual analytics models. These visual analytics models make it easy for anyone in the business to evaluate the data and see what is occurring. Furthermore, businesses can use the platform to create interactive reports and dashboards, allowing them to quickly summarise key performance metrics for anyone in the business. Finally, the SAS Viya allows for everyone – data scientists, business analysts, developers and executives alike – to collaborate on data in real-time and deep dive into it.

From traditional analysis of variance and linear regression to Bayesian inference and high-performance modelling tools for massive data, SAS’ statistical analysis software meets both specialised and enterprise-wide statistical needs.

If you want to find out more about SAS’ statistical analysis software, please click here.

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