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The 21st century has seen some big developments in data analysis. It’s seen:
- The birth of the cloud – arguably in 2000
- The development of Big Data – in 2005
- The creation of technologies such as Hadoop (2006) and Spark (2014) that allowed computation on enormous data sets
Today, another strand of tech is beginning to refashion the world of data analysis. That strand? Interactive technology. In this article, we’ll look at the ways interactive technology is making its mark.
Interactive technology in a nutshell
What do we mean by interactive tech? Firstly, it’s technology that digitally facilitates interaction between people or allows for user content manipulation. Secondly, it’s systems that support a user’s task performance in a collaborative way.
Six Ways Interactive Technology is Revolutionizing Data Analysis in 2019
1. Creative Analysis in Team Time
While outsiders may imagine the role of a data scientist to be a solitary one, in 2019 the opposite is actually true. The best data analysis reportedly occurs when people work as teams. Now, one particular bit of interactive tech is transforming team time and collaboration for data analysts.
That tech? Interactive displays. Here’s the deal, interactive displays are screens that connect to the cloud as well as portable devices like laptops and mobile phones. Any information displayed on these screens can be manipulated by touch and annotated on screen, too.
So why exactly are these revolutionizing team time? Well, scientists at The University of Iowa have shown that humans remember things they see and touch better than things they hear.
So, when plans, reports and other data is presented visually in team meetings, it can lead to more creative thinking and higher-level problem solving due to the load being taken off the short and long-term memory systems.
2. Efficiency
In 2019, more and more companies are starting to link their data sets with interactive voice technology such as Amazon’s Alexa, so they can get real-time responses to data questions without having to lift a finger.
Today, companies like Sisense offer the linking of data and interactive voice technology as a service. Needless to say, this particular use of interactive technology can save data analysts the hours they would normally waste scrolling through screens and reports for answers to queries.
3. Faster communication
It’s thought that the average 35 to 50-year-old takes 24 minutes to respond to an email. Interactive technology like Slack, Rocket.Chat and Flowdock has been shown to reduce the number of emails sent within a business by 48.8 per cent.
So, while the team chat phenomenon isn’t specific to the data analysis industry, it’s even more important for data analysts to get immediate answers to their questions, because some data sets can change on an hour-to-hour basis.
4. Intelligence Pooling
One of the major benefits of interactive technology is its ability to make it easy for people to collaborate on projects remotely, from all around the world.
In fact, video chat platforms such as Zoom and Skype make virtual meetings as effective as face to face ones. Today it’s as simple for data analysis experts from Stanford University in the USA to collaborate with those from Erasmus University Rotterdam as it is for two experts to chat over a meeting room table.
5. Democratization of Data Science
Recently, David Robinson, the chief data scientist at DataCamp, wrote about how the democratization of data science was the most exciting thing about the future of data analysis.
In his article he talked about the growth of the number of people using platforms such as Python and R for data analysis and how programming and statistics education was becoming more and more accessible. This accessibility has, in part, been brought about by interactive technology.
Today those interested in learning about data analysis don’t need to go to universities, like those mentioned above, to learn about the practice in person. Instead, they can learn the basics and beyond through interactive online courses with titan institutes such as the London School of Economics.
6. Workflow Management
2019 is the year of streamlined and transparent workflow. Project management platforms such as Trello and Jira have never been more popular. The stats? Trello alone has close to 100 million users.
While this phenomenon isn’t specific to the data analysis world, it’s still making waves. Point in case: Kaiser Permanente.
This health care company employs more than 22,000 workers and it uses Jira to manage its data analysis tasks. Talking about how he uses the system, Brian Sikora, director of analytics at Kaiser Permanente said:
“If you think of an industry with incredible amounts of data, healthcare should be one that springs to mind. And in an organization the size of Kaiser Permanente (KP), analytics must be used to inform every part of the business. Using Jira Software as the core of an Analytic Request Management (ARM) solution is a unique use case. Designed to increase collaboration and transparency in analytic work across the organization, the ARM system is standardized to enable reporting across multiple departments but also allows for customization according to departmental workflows.”
To Sum Up
Interactive technology is revolutionizing the way data scientists do their jobs in the following ways:
- Increasing the creativity and higher-level thinking of teams
- Improving efficiency in data mining
- Making communication faster
- Allowing experts to collaborate from remote locations
- Making data analysis more accessible
- Making workflow more streamlined