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3 issues standing in the way of self-service analytics
A major obstacle blocking self-service analytics is the lack of user-friendliness and flexibility of many analytics tools.
Milo Davies, SAS principal solutions specialist, shares his insights on three key issues facing self-service analytics
and how the SAS Viya platform is helping to solve the problem.
By Anna Pelesikoti, SAS Australia & New Zealand
Analytics is becoming an increasingly essential capability for organisations today, but many businesses are finding it a tough egg to crack - particularly with the growing demand for self-service analytical tools. According to a study by Aberdeen Group, nearly 60 per cent of organisations do not feel they have adequate access to their data in a self-service capacity.
1. Analytics tools must be adaptive
Businesses are increasingly turning to the cloud for many of their day-to-day IT needs - from key software platforms to data storage, and many areas in between.The shift from on-premise to cloud means analytics tools need to be not only cloud-friendly, but adaptive to support this move. An analytics platform that can be rolled out on-premise or within different cloud systems - and easily moved between them - eliminates this problem.
"Viya has been designed from the ground up to make it really easy to deploy into different environments, whether that's on-premise or into private or public clouds," Milo notes.
"It's also very easy to lift and shift a Viya implementation from one deployment environment into another."
Viya's adaptability extends to all stages in the analytics lifecycle - from gathering data through to exploring and manipulating it, applying analytics to business problems, and deploying the insights into an operational context.
"Viya is designed for all of those different parts of the analytics lifecycle and is able to adapt to an organisation’s changing data or user volumes, or as their analytical maturity develops," Milo explains.
SAS Software (@SASsoftware) Sep 12, 2016
2. Tools must be accessible to multiple end users
Throughout its growth as a major business tool, analytics has traditionally been in the hands of trained, specialist users. Self-service requirements, however, necessitate any analytics solutions be open and accessible to users throughout an organisation.
"The business wants the flexibility to do more things with their data because they are simply more data savvy than in the past, and are becoming less reliant on IT," Milo says.
"The notion of self-service data prep and wrangling is something our customers want to do more of, so we're building it into the Viya platform, along with advanced machine learning algorithms that are accessible to people who aren’t necessarily full-blown data scientists and programmers."
With SAS Viya, code in Python, Java or Lua - or skip the code entirely.
Viya also opens up the underlying analytical engine to non-SAS languages, letting users leverage Viya from programming languages they are familiar with such as Python, R, Java and Lua. In this way, Viya can break down the barriers of a heterogenous analytics landscape - by allowing different analytics teams with different skills sets to more easily collaborate.
3. Analytics must be agile enough for business needs
Without the ability to get results quickly, businesses tend to only use analytics to better understand past performance instead of informing current decisions. Through self-service analytics, organisations are able to empower their staff to find insights and act on them in a timely manner.
"If you don't have that capacity to derive insights out of your data in a timely way, then you're going to miss the boat."
Principal Solutions Specialist,
SAS New Zealand
"To compete, organisations have to be able to find those insights faster and act on them more quickly. If you don't have that capacity to derive insights out of your data in a timely way, then you're going to miss the boat," says Milo.
SAS Viya’s agility is thanks to an MPP (massively parallel processing) architecture, which accelerates all phases of the analytics lifecycle. This not only results in faster generation of insights, but also allows for more advanced and automated machine learning algorithms that can produce more accurate predictions. This speed and accuracy, translates into better business decision making.
Why SAS Viya?
To keep up with industry demands - and the needs of business users - analytics tools need to be flexible and intuitive.
For over 40 years, SAS has been a pioneer in the analytics sphere, and SAS Viya sharpens that edge. In The Forrester Wave: Enterprise Insight Platform Suites report, SAS was the only vendor to qualify as a technology leader, thanks largely to Viya's capabilities.
To learn more about SAS Viya and enable self-service analytics for your organisation, contact us today.