Embrace Open Source with Open Arms via SPSS

Share this post:

Data Science skills are some of the most valued globally. Statistical Analysis and Data Mining are the second most in-demand skills globally for the second year in a row, according to LinkedIn. Like SPSS these are essential to successful data science.

 Skills to Pay the Bills

No matter where you’re doing data science for, you need to know how to use the tools of the trade. This means a statistical programming language, like R or Python, and a database querying language like SQL. These skills are growing more and more essential. For data scientists, and almost every data science role, you need to know R, Python or both.

Tilt the scales (!) in your favour with Python skills

R and Python are the two most popular programming languages used by data analysts and data scientists, with Python the top programming language for 2017and R the sixth. Both developed in the early 1990s, free and open source, the two have a lot in common. You mainly use R for statistical analysis and Python as a general-purpose programming language.

Open source technology defines these high-demand skills. But organisations still value the integrity of their data and want processes and outcomes that fit their business need. How do we combine the two?

 SPSS Integrations

The two latest releases of IBM’s SPSS tools, Statistics and Modeler, further deepen the link between the proprietary software and open source tools. This gives data scientists the best of both worlds.

With its latest release, version 18.1, SPSS Modeler introduced additional functionality to its already extensive integrations with R, Python and Spark. Allowing you to bring open source flexibility to the non-coding environment, Modeler 18.1 introduced three nodes that run Python algorithms — one-class SVM, SMOTE and XGBoost. These well-regarded algorithms, first only available via Python coding, are now exposed directly in the Modeler GUI. The latest version even ships with Python 2.7.

Use advanced data analysis with SPSS Modeler and Open Source tools to find hidden patterns in your data

And it is not only Modeler that has extensive links with open source tools. SPSS Statistics allows you to enhance SPSS Syntax with both R and Python through specialised extensions. You can leverage over 130 extensions, or build and share your own to create a customised solution.

Accessing SPSS allows you to merge the knowledge and tools available with this known and respected software, while keeping with the latest developments in data science with its close links to open source. Take advantage of these integrations and try out SPSS today.

Technology Service Providers Sales Leader, Nordic

More Analytics stories

How tech-enabled finance will accelerate the transition to net zero carbon emissions

On the path to global net zero carbon emissions, the finance industry is a key driver while technology is an enabler of sustainability. To make meaningful progress to mitigate climate change, the global finance industry needs technology to quantify climate risk and mobilise investments. Financiers also must adopt collaborative, secure and trusted data platforms, and […]

Continue reading

Aqua farmers are giving back to the oceans – with technology

Our oceans sustain us. They give us oxygen and they capture carbon dioxide. They feed us and they provide a wage to 40 million people across the world. They bring us joy and they show us beauty. But we are not sustaining our oceans in return.  We are taking more from them than can be replenished. We […]

Continue reading

How a supply chain attack closed one of Sweden’s largest supermarket chains

Last week, when heading out for some groceries, I was met with a note on the entrance to my local grocery store saying the store was closed due to IT problems. Working in IT security this immediately sparked my curiosity. What was going on? I quickly pulled up my mobile phone to check the news. […]

Continue reading