In this guest article from Australia’s James Cook University, experts discuss the latest key trends in data analytics. Read on to stay abreast of the latest innovations and leaders in the field.
The demand for data has increased exponentially in the past decade. Businesses have only just begun to realise the potential goldmine of information available online. Using the summarised data is one thing, knowing how best to collect, collate and disseminate it is quite another. Thus, data analytics professionals are highly sought-after, with data science jobs frequently appearing on LinkedIn’s list of most in-demand roles.
Australia’s James Cook University offers a Master of Data Science degree program.
While corporations work to fill the gap, they are also increasingly investigating applications and programs that can streamline data analytics processes, making data collection and use more simple and efficient. As a result, the industry is expected to be worth over $128 billion by 2022, a predicted 36 per cent growth from 2016.
In the scramble to get ahead, a few trends are asserting their dominance. We’ve unearthed the top data analytics trends set to see the industry surge ahead.
Data management technology
The rise of the Internet has facilitated the increased availability of data. Artificial Intelligence programs such as Suri, Alexa and Google Home all provide new and exciting options for data collection. So too does the rising demand for the Internet of Things, with smart watches collecting health data and interactive technology such as smart fridges revealing consumer behaviour.
As our data science jobs and capabilities grow, data management technology becomes even more crucial. As Emily Washington of Infogix notes: “Businesses are increasingly evaluating ways to streamline their overall technology stack if they want to successfully leverage big data and analytics.” With increasing media buzz about privacy breaches, the key to long-term data management is not only selecting the right application, but finding skilled individuals able to work with a number of data sets and management programs, who can troubleshoot on the ground when required.
Collaborative platforms
For digital-centred businesses and large corporations, data teams have the potential to grow to significant sizes. Interconnected businesses may also have teams on different sides of the country,
or the world. Collaboration needs to take place on strong, internal networks that enable different teams to work in tandem to achieve different aims with the same information.
Collaborative platforms such as Dataiku have answered the call. This program enables connections to over 25 data storage systems, and enables highly-complex analytics to be conducted and communicated on a businesses’ network. The platform can then be used by businesses to create their own data collection software using existing science and cutting-edge machine learning strategies. All data analytics teams need to do is cultivate effective teamwork and cooperation systems, and they’re well on their way to success.
The ability to bring it all together
These collaborative platforms can’t have strategic impact if there aren’t individuals equipped with the right skills to understand the data and how best to utilise it. Tomer Shiran, of Dremio, has suggested that the role of ‘data curator’ will soon come to the fore of the industry. Data curators would blend the skills of those who read the data, and those who transform and transmit it. The skills required would include high level critical thinking, as the curator will constantly be making decisions about the utility of each data set. They will also hone their knowledge, in order to make the most correct judgements as to what data to collect, and where it should be employed.
Realize your full potential and discover data analytics
If the potential applications of data analytic technology get you excited, why not consider a Master of Data Science from James Cook University? With a flexible, fully online course that will link you to fellow professionals, there’s really nothing to lose.
Find out more on the James Cook University website today
It’s true that in today’s technical and Internet-savvy world companies are faced with an overabundance of data. Companies can use this information to help make strategic decisions, but not unless the data is organized. Data warehouses can help with that because they let companies optimize and organization information from multiple sources for analysis and reporting, which can then lead to gaining insights that will help make important strategic decisions.
The number of companies re-thinking strategy and wanting to leverage #data and #AI is certainly growing. This is a good reminder that data, infrastructure, user experiences and strategy are all closely connected. I strongly encourage all business leaders to be involved in the discussion and not just leave this to the technical teams.
Great insights, Stephanie! The evolution of data analytics, as highlighted in your article, truly showcases the transformative power of data in today’s business landscape. At Data Expertise, we closely monitor these trends and have observed the increasing significance of AI-driven analytics in enhancing decision-making processes.
To add to your point on collaborative platforms, we’ve also noticed a surge in demand for transparency and interpretability in AI models, especially in sectors like healthcare and finance where decisions are critical.
For those intrigued by the intersection of AI and data analytics, we’ve compiled some cutting-edge case studies and expert analyses at dataexpertise.in. These resources delve deeper into how businesses can leverage AI to unlock the full potential of their data. Feel free to explore and join the conversation on the future of data analytics!