Organisations around the world have been experiencing unprecedented challenges to survive during the COVID-19 pandemic.
The workplace is now a minefield of financial and operational challenges impacting on the requirements of their staff, their customers and their suppliers. With the rise of remote working and at home conferencing, organisations have, through necessity, been looking to digital technologies to address their needs and those of their employees, whilst retaining the need for ensuring safety.
I am sure we have all seen the rise of the social media use during the pandemic and how it has brought together people from around the world in ways that seemed impossible just a few years ago.
From chatting with granny and her first time social media apps to whole orchestra’s performing live to the world, digital technology has transformed the way we work and play. With this in mind, we have scheduled a Big Data and AI Toronto Virtual conference later this month that will be held exclusively online.
What are the Big Data Technologies?
If we have learnt anything from this past year it is that the abilities of the Internet and digital technology are a huge, integral part in the lives of the world citizens. Also, that this trend in remote working, rest and play can only grow. We have also seen a massive increase in the amount of data being generated that is capturing information from the populations online use. To make sense of the information from our digital footprint within this huge complex and ever increasing medium, groundbreaking technologies are needed to analyse, process and extract the information.
That is where Big Data Technology, a rapidly expanding and increasingly relevant system is making huge advancements. These systems can be divided into two classifications.
1. Operational Big Data Technology. This is the day to day data that an individual generates through their use of social media, shopping transactions or even just their browser history. Operational data is also generated within businesses from the processes and systems of their operations. This can be from computerised logging on and off systems to scanner-based sales registers, digital ordering packages to online booking sales. It is also to be noted that data of this nature continually changes and therefore businesses are provided with expeditious and up to date information that is the driving force behind the second classification, namely.
2. Analytical Big Data Technology. This is where the clever stuff happens. Big Data Analytics s the scrutinising of the huge amount of data generated by the operational data to find hidden patterns, interrelationships and affiliations as well as various other observations and trends. Businesses have always used basic analytical methods to determine their business needs but they used too much pieces of paper, time and brain power.
The beauty of big data analytics is the speed and efficiency with which it is possible to identify new business goals and potential new markets. This ability to work in a more cost-effective and timely manner is giving businesses the competitive advancements they did not have before.
However, with Analytical Big Data Technology, there is no one specific technology that can be applied to all the Big Data. There are various types that can be brought together to allow businesses to glean valuable information.
a. Data Management and Data Mining, two processes whereby there is a programme in place for the collecting, collating and protection followed by a programme of systematically examining the large amount of data, removing irrelevant and/or repetitive data to establish what is pertinent and appropriate.
b. Text Mining allows the analysis of text data from the web, discovering new trends and topics that may have been overlooked in previous sweeps through the internet. This uses machine learning or natural language processing to scour the internet.
c. In-Memory and Predictive Analytics. In-Memory is the use of your system memory to test new scenarios and create testing models, whereas Predictive analytics uses historical data to run statistical algorithms and machine-learning techniques.
d. Machine Learning. Where science fiction meets science fact. Machines that learn. An application of artificial intelligence (AI) that has the ability to automatically learn without specific programming. The machine accesses the data, identifies patterns and provides decisions for future consideration based on semantic analysis through the understanding of text.
How to Attend the 2020 Conference?
Now that life is returning to the new normal, the Big Data and AI Toronto Conference is to embrace the new technologies and go virtual. This means that this year’s conference attendees will be able to connect, virtually, wherever they are in the world, giving them access to a wide-ranging programme of events. It is simple to look at data providers and industry experts on 29th and 30th September 2020 by visiting our website. All the details of the conference programme, events and virtual exhibition are available there for you to peruse as well as all the information needed to register your virtual attendance.
A Final Word
If there is one thing that the past few months has highlighted it has to be how the population of the world has had their eyes opened to the world wide web. From buying the groceries to using VR and AI to decorate a house, home and homeworking to running global companies in their pyjamas, people have discovered the simplicity and convenience of the humble computer. This interaction has created an explosion of useful information that is Big Data.
Now is the time to find out how companies are using Big Data for development and expansion. From stock markets to retail, space exploration to railway tickets, the data is there and just waiting to be taken on advantage by you and your company.
