Technologies like ML have proven to be extremely useful tools for Data Scientists to derive valuable insights from existing data. However, these Data Scientists have previously been spending a large portion of their time finding the data they need and making sure it’s in a usable format. Data Virtualisation offers a new way to address these problems in a much more agile and efficient way.
For a number of years now, organisations have been copying data from a range of systems into a centralised data store in an effort to move away from data silos. Data Warehouses and Data Pools can be a good way to manage this, however they can be expensive to manage and may also have a higher margin of error, due to the manual processes involved in extraction and importing. As a business, managing 20 or 30 different unique data sources can be a significant challenge, which is made even more difficult when that data is inherently difficult to procure.
Data Virtualisation follows a process that connects to a data source, combines a range of different data types and gives the ability for business users to consume the data through dashboards, dynamic reports, portals and apps. This process aims to deliver a holistic view of information about your organisation to business users across a range of source systems.
Data Virtualisation can also simplify analytics processes as you’re always querying the source data in realtime.
When addressing the issues of data integration – Data Virtualisation is the answer to what many businesses have been looking for. What makes it different from other solutions is that Data Virtualisation keeps data in source systems and instead delivers a unified view of the various data sources in one place. As business users explore and extract reports, Data Virtualisation accesses the data in real time – demonstrating that joining data is the most efficient and useful way to manage data.
What are the key benefits of Data Virtualisation?
• No Need To Replicate Data: Integrated data views draw from a range of sources without having to duplicate or move it – bypassing busy work, version control issues and cutting down on data storage.
• Access In Real-Time: The latest version of data is instantly available.
• Unified Data Security: All data, from source to output, can be queried through a single virtual layer. This inherently exposes any security issues and achieves consistent integration.
Getting Prepared for Data Virtualisation
Know your data – having a comprehensive inventory of all your datasets, their locations and their requirements is key, as each one will need instructions to ensure they are fully engaged with the virtualisation layer. Artificial Intelligence and Machine Learning can help significantly with this part of the process.
Advanced Analytics Makes It Happen
Advanced Analytics has a huge emphasis on speed and an almost limitless potential to process and visualise vast amounts of data in real-time.
Like any tool, it’s only as good as it’s application and increasingly, many industries are discovering the virtually limitless applications of Advanced Analytics.
The insurance industry, in particular, has been an early adopter in finding new ways of applying advanced analytics to assist in reducing incidences of fraud, by using predictive analytics that integrates statistical models. This predictive modelling autonomously scrutinises trends of fraud by also using historical data to forecast risk. The entire insurance industry is based on risk, the better these risks are understood through insights, the better it can be actioned upon.
For smarter (& faster) intelligence
Brytlyt systems are used in a variety of Big Data applications at the very cutting edge of the transformational analytics revolution, including Machine Learning, Deep Learning & Advanced Data Science.
Powered by GPU Acceleration
Advanced Analytics takes advantage of the power and performance of GPUs (Graphics Processing Units) instead of relying solely using CPUs (Central Processing Units). This accelerates process-intensive tasks across a variety of industries, including (but not limited to) insurance, financial services, telecoms, pharmaceuticals, defence, logistics and beyond.
CPUs are highly versatile and good at handling multiple tasks, however GPUs are typically far more powerful and can handle a few specific tasks incredibly well – making them perfect for taking on repetitive and specialised computing tasks at speed.
GPU-accelerated systems are also inherently well suited to provide interactive visualisations in real-time for enormous datasets.
Why use Brytlyt for Data Virtualisation?
- Brytlyt helps you interactively query, visualise and power data science workflows over billions of records with a wide range of accelerated analytics solutions.
- Our end-to-end platform delivers decision support and business intelligence offers critical insights.
- Built on PostgreSQL, we empower users to analyse more data, faster, and with ease.
Brytlyt aims to generate smarter intelligence, quicker
We understand the importance of data-driven business and can help you achieve it, so you’re able to find patterns and insight across huge amounts of data, in an instant.
At the forefront of the Advanced Analytics revolution
Our unique GPU patent pending IP technology has been developed to be at the very forefront of the transformational analytics revolution. Our next generation platform with ‘speed of thought’ analytics is built for ambitious businesses who want to harness their rapidly growing datasets of today and for tomorrow.
We know data; and we know how to help businesses get the most out of huge amounts of data, in an instant.
A truly smart integration
Instead of overhauling existing systems, our platform can be easily integrated into most business environments. Brytlyt is the future-proofed approach to data processing and analytics.
Tomorrow’s technology, today
Brytlyt is the future-proofed approach to data processing and analytics. Instead of overhauling your existing system, our platform can be easily integrated into your business environment. Plus, its adaptable functionality means you can continue to develop the platform as your needs change.
To learn more, or for any enquiries, contact us here.
