Fundamentally, people respond far better to visual representations of data. This has led an entire industry of software providers and platforms to enhance the data visualisation journey over the past decade, building upon an ever growing stream of data points and volumes.
The majority of enterprises now understand how important data visualisation is, as well as the systems on which it is built.
There is no doubt that data dashboards and similar tools we use to represent data have advanced massively over the last decade or so. However, as Gartner’s recent report on the top 10 data and analytical trends of 2020 notes, we are moving beyond the era of the well-known data dashboard. New innovations in data representation are now taking over with their ability to tell automated, interactive stories for all types of data that are moving far beyond that of many established techniques.
According to Gartner, the rise of visualisation innovations that embrace advanced AR/VR, augmented analytics, AI/ML, structured and unstructured data sources, NLP and so on, will cause a “shift to in-context data stories …[meaning] that the most relevant insights will stream to each user based on their context, role or use”.
The good news is real-time data visualisation tools (as well as other advanced analytics functionality) is now becoming more accessible than ever.
Improvements in Data Processing Makes This Happen
The delivery of high performance data loading is the foundation for faster and more efficient data analytics and data visualisation. It’s the fundamental step that must be acknowledged in order to deliver the best user experience for any accelerated data analytics process.
The Data Bottleneck
Looking into these increasingly powerful tools to represent and overlay the ever-growing sources and volumes of data, such as with the wide-scale adoption of IoT, the onward march of social media, as well as the more traditional data sources held within businesses, there’s now a need to access data like never before. Taking advantage of these tools will enable you to stay ahead of the competition in our ever more data-driven world.
Data loading has to be performed by every analytics solution. It’s the critical process of uploading all datasets that have been collected by your business into a platform that can help transform them into insights. It’s a process that happens continuously in the background, occurring every time users want to analyse new data or change the dataset they’re working with.
Traditionally, large datasets have previously had to be pre-defined, pre-aggregated and preloaded for the given data you are looking to visually represent and query. This is by nature restrictive as in itself, only specific questions can be posed and only performed on the pre-loaded data available. Furthermore, this is inherently a time-consuming process that requires specialist resource dedicated to the data set builds, the flexibility of which will be limited by the quality and availability of this resource. This also incurs a cost to the business – both in terms of the utilisation of the specialist resource and by the lack of agility that a business will have, relative to its competition.
GPU-accelerated systems change the entire process of data loading. Instead of using traditional (and significantly slower) CPU-based architecture, GPU-accelerated systems take entire datasets into the system, enabling users to instantly interactively visualise, query and power data workflows over billions of lines of data.
Load Accuracy & Increased Data Alignment
Being able to load data accurately from a database into an analytics platform is a common pain point for analytics users. All too often, data inaccuracies rise – such as mismatching tables, causing uploads to fail. Often, this forces users to practically start from scratch – spending unnecessary and precious time repairing their data.
Speed
As the first process you undertake, data loading has to be fast. Not just for a better overall experience, but the faster you upload your data, the quicker you can find and fix any errors found. However, achieving fast data loading can be a challenge; especially when working with enormous datasets.
The speed and data processing power that’s available from GPU acceleration has completely reshaped IT architecture over the past few years, with the ability to scale resources based on immediate (and even future) requirements.
I recently read a great article on this topic that you can find here
Over the next few years, the vast majority of organisations are expected to have cloud based systems to meet their data, infrastructure and software needs.
The Future of Data Visualisation & Data Storytelling
Over the next few years we can expect to see BI (Business Intelligence) and AI (Artificial intelligence) working together to create augmented analytics and augmented data. This looks to deliver Automated Insights (also known as ‘data-based storytelling), Automated insights illustrates key findings in a more autonomous way, relieving the need for busy work to prepare compelling visualisations for stakeholders.
Self-service BI looks to give end users the ability to generate more dynamic reports that will give actionable insights with AI enhancements, to include automated search engine reporting, augmented data preparation and more.
In addition to this, Cloud-based & Mobile BI is expected to surge, as partial and full-time remote working continues to be the new normal for a significant number of companies even in a post-pandemic world.
Solutions
Deploying specialist platform providers can significantly expedite data processing with advanced GPU accelerated databases, for data performance at scale. Many practical considerations to businesses have already been thought of, including the ability to complement existing database infrastructure so businesses aren’t in a situation where they have to rip up and replace what they already have, but will have the access to the next generation of advanced data visualisation and data processing tools.