Don't Panic! It's Just Data

Data discovery is a subset of business intelligence (BI), referring to the collecting and consolidating of data from multiple databases into a single source.

This makes it much easier to investigate and detect patterns, as well as apply real-time data controls to ensure safe storage and analysis.

In this third episode of the three-part EM360 Podcast, Analyst Christina Stathopoulos is joined by Richard Heyns, Founder and CEO of Brytlyt, to discuss:

Scaling analytics speed

How to optimise the processing of geospatial data

The next generation of BI

Location Intelligence (LI) is how we use data to answer spacial questions. It goes beyond visualising data on a map - in fact, the analysis of location data has become integral to our daily lives.

From 5G network deployments and geomarketing to Dominos Pizza understanding where you are and what you’re likely to order as soon as they pick up the phone, it’s clear that every sector is adopting LI to strengthen their processes.

In this episode of the EM360 Podcast, Ciaran Kirk, Operations Director at IMGS joins Analyst John Santaferraro to discuss Location Intelligence aspects such as:

Newest trends in data integration

Streaming data challenges

Modern data pipelines and what they give enterprises

The trend of data at our fingertips is continuing. Virtually, everything we do is impacted by data. 

From driving your car to shopping to fighting pandemics such as Covid-19. Everything is impacted by data and understanding is improved by embracing and using it 

Data powers many technologies and itself is neither good nor bad. As data influences more of our life, we have to ensure that we use it responsibly so as to improve the lives of everyone from customers, employees, citizens, and the planet we all live on. We face many challenges and data plays a critical role in helping us make the best decisions.

In the last episode of a three-part podcast series with Safe Software, Analyst Susan Walsh speaks to Don Murray, President and co-founder of Safe Software, to explore:

• How data was critical in the fight and management of Covid 19 around the world. 
• The importance of using data responsibly so that people and organizations understand the often unintended consequences of their actions.    
• The critical role of data is to drive decisions to meet the challenges we face as individuals, organizations, and a planet. Our future depends on using data.

There is no time like now for all of us to embrace data.

The trend of data at our fingertips is continuing. Virtually, everything we do is impacted by data. 

From driving your car to shopping to fighting pandemics such as Covid-19. Everything is impacted by data and understanding is improved by embracing and using it 

Data powers many technologies and itself is neither good nor bad. As data influences more of our life, we have to ensure that we use it responsibly so as to improve the lives of everyone from customers, employees, citizens, and the planet we all live on. We face many challenges and data plays a critical role in helping us make the best decisions.

In the last episode of a three-part podcast series with Safe Software, Analyst Susan Walsh speaks to Don Murray, President and co-founder of Safe Software, to explore:

• How data was critical in the fight and management of Covid 19 around the world. 
• The importance of using data responsibly so that people and organizations understand the often unintended consequences of their actions.    
• The critical role of data is to drive decisions to meet the challenges we face as individuals, organizations, and a planet. Our future depends on using data.

There is no time like now for all of us to embrace data.

Deep learning is a subgenre of machine learning and AI that mimics human behaviour - lending itself to predictive modelling and statistics. 

But how can we take the power of deep learning and make it more accessible to the citizen data scientist?

In this episode of the EM360 Podcast, Analyst Christina Stathopoulos speaks to Richard Heyns, Founder and CEO of Brytlyt, about:

• Deep learning and artificial neural network systems
• DL vs ML
• Embedding AI into the database

Machine Learning Operations, or MLOps, is a set of practices that aims to deploy and maintain machine learning models reliably and efficiently.

Similar to the DevOps approach, MLOps seeks to increase automation and improve the quality of production models while focusing on business requirements.

In the first part of this three-episode series on the ‘Transformational Serverless Acceleration for Analytics’, Analyst Christina Stathopoulos speaks to Richard Heyns, Founder and CEO of Brytlyt to cover:

• Why do two-thirds of models built with the intention to deploy never make it to deployment
• Databases and the critical role they play
• Scaling up analytics and ML

Artificial intelligence. The catch-all term defines the machines that can mimic and display sentient cognitive skills such as learning and problem-solving. A key part of modern technology, the advancements of AI indicate just how far the human race has come.

AI can be used by businesses to interpret and use massive volumes of data.

In this third episode of a three-part EM360 podcast series with Findability Sciences, Data Whisperer and Analytics Expert, Christina Stathopoulos speaks to the company’s Founder and CEO Anand Mahurkar, as the pair explore:

• Getting the most out of wide data
• Bringing the power of AI to traditional automation solutions
• Calculating ROI for AI projects

Digital twins are virtual models designed to accurately reflect a physical object or process. The real-world applications of this are endless - from city planning to construction and decoration, digital twins can help you visualise concepts within spaces with ease. When it comes to processes a digital twin can represent measurements of flows that are difficult to show such as wind direction, or temperature of flows within pipes.

What’s more, the twinned object can be outfitted with sensors and produce performance data that can be applied to the digital copy. This offers a valuable insight into how the physical object will perform in real life.

How do digital twins relate to spatial data?

In the second episode of a three-part EM360 Podcast with Safe Software, President Don Murray speaks to Susan Walsh, Founder and MD of The Classification Guru, about:

• Digital twins and the evolution of spatial data
• What expertise and requirements are needed to create a digital twin
• The potential that lies in digital twins for the future and how they can move society forward

Data democratisation is the continuous process of enabling company-wide access to data, regardless of technical know-how, in a bid to spread a data-led decision-making mindset across all departments of an organisation.

It can be a big challenge - and serious investment - for companies as employee education and tool implementation is not trivial undertakings.

How can companies set up their data democratisation strategy?

In this episode of the EM360 podcast, Content Producer Matt Harris talks to Giuseppe Mura, Director of Solution Engineering at StreamSets, as they tackle:

• The steps companies should utilise to set up their data democratisation strategy
• How the demand for DataOps will be affected as businesses adapt their data integration processes
• Bringing in non-IT-native and non-DevOps experts and providing them with everything they need

While we have made huge steps in transferring information into processes of data analysis, there is still a huge reliance upon hard-to-process document-based information. One of the biggest culprits of this is the healthcare industry. For decades, they have been using this outdated, insecure method of managing patients' private information, which has led to multiple issues, such as data breaches. The restraints of paper-based forms and documents are further highlighted by the problems that arise throughout workflows: misplaced document-based information; slow delivery times as information has to be passed through multiple different parties.

Simplifying Processes of Data Analysis

On this podcast, Greg Council, VP Marketing and Product Management at Parascript, joins us to discuss the processes of document-based information and why current systems are so outdated. He also outlines how we can best move to a more automated form of operating and what it means to view document processing from an insurance perspective. Listen and learn about:

Fundamentals of the healthcare and health insurance market

Key challenges around claims-to-payment, also known as revenue cycle management, and the inclusion of documents in the workflow process

The impact of numerous parties being involved in a manual automation process

The role of NLP in converting complex document-based information into structured data

Auto-adjudication and its importance within an automated workflow

The implications of non-structured electronic data interchange (EDI) in terms of cost, time, and process

Practical advice on where to start with document automation