Data Phine

24/02/2022

LiDAR is an active optical sensor technology which scans the earth’s surface to determine highly accurate x, y and z measurements. It transmits laser beams to a specific object and reflects its movements back to the receiver and analyzes the time span and distance with GPS and INS information to construct a 3D point cloud of reflective obstacles. LiDAR adds complementary information and is very strong at detecting pedestrians and other non-metallic objects at night, a scenario in which camera and RADAR sensors often fail.

16/02/2022

Discover proven techniques for developing safer, more efficient transportation. Learn about advancements in autonomous driving, end-to-end vehicle simulation, robotaxis, trucking, mapping, and more.

15/02/2022

Computer Vision: The scientific field of computer vision studies how to extract, analyze, and understand information from images and video.

27/11/2021

This course presents a gentle introduction into the concepts of data analysis, the role of a Data Analyst, and the tools that are used to perform daily functions.

Sign-up here: https://rebrand.ly/dataphine

What will you learn?

you will learn about the different types of data analysis and the key steps in a data analysis process.

You will gain an understanding of the data ecosystem and the fundamentals of data analysis, such as data gathering or data mining.

You learn to use data visualizations and dashboard tools.

You will then learn the soft skills that are required to effectively communicate your data to stakeholders, and how mastering these skills can give you the option to become a data driven decision maker.

You will gain an understanding of the different components of a modern data ecosystem, and the role Data Engineers, Data Analysts, Data Scientists, Business Analysts, and Business Intelligence Analysts play in this ecosystem.

You will learn about the role, responsibilities, and skillsets required to be a Data Analyst, and what a typical day in the life of a Data Analyst, understand the different career paths that are available for data analytics, and identify the many resources available for mastering this profession.

You will learn data Storytelling and the important.

You will know to differentiate between the roles of a Data Analyst, Data Scientist, and Data Engineer.

You will be able to summarize the data ecosystem, such as databases and data warehouses.

This course does not require any prior data analysis, spreadsheet, or computer science experience. All you need to get started is basic computer literacy.

Enroll for Free!
Sign-up

https://rebrand.ly/dataphine

18/10/2021

18/10/2021

One of the reasons that data science projects can fail or lose
investment is because they aren’t aligned with business goals.
Therefore, they don’t deliver value that is understood by the
broader organization.
To be able to show business value, you must identify projects
that ladder up to business priorities. While a project may be
interesting or valuable in another way, if it doesn’t help achieve
identified business goals, it is going to be an uphill battle
securing stakeholder buy-in and showing meaningful results

13/10/2021

Pandemics, analytics and politics: how data-driven AI makes better policy

Dr Nuria Oliver’s algorithms model the perfect politician, one who can make accurate and cost-effective policy responses amidst the chaos of a COVID-19 outbreak. Could this start a new global trend: evidence-based policymaking?

With the public weary of lockdowns, hospitals overloaded, vaccine shortages and policy-makers drowning in the chaos of a COVID pandemic, Spanish data scientist Dr Nuria Oliver knew that mathematics and big data could make better decisions than a human politician.

Her team got to work building big data models to forecast the incidence of COVID-19 and cost-effective policy interventions to minimise death, economic havoc and spread of the dreaded disease.

The model took 12 different ‘dimensions’ - or interventions such as closing workplaces and schools, mask-wearing and education - so the AI modelling could spit out the very best policy intervention given the hospital loads, economic costs and testing capabilities.

“When you look at the 12 dimensions, there were different activation levels which led to 7.8 million possible combinations,” explains Dr Oliver, who has published hundreds of research papers and developed more than 40 patents for data-driven solutions.

“No politician could likely comprehend those 7.8 million different combinations but a machine can - a machine can find the policy that satisfies the outcome against the given cost so it’s always offering up the optimal policy. It’s evidence-based policy making.”

AI helping humans
Dr Nuria Oliver - who is speaking for IAPA on May 6 - and her team, ValenciaIA4COVID, have been declared the world’s winners of the $US500,000 X Prize, which saw them create models for 236 countries to help navigate COVID-19.

“The models can make decisions that are not based on political interests or instinct but on the evidence of what the data is telling you,” Dr Oliver says.

“The system proposes policies with the best cost-benefit tradeoff so if your hospitals are empty, then you might want to open up a bit or if the hospitals are full, you would probably need to implement stricter interventions to contain transmission.”

Dr Oliver’s complex models take into account different measures but the final challenge to win the prize was to make an “artificial politician” - also called the prescriptor - to recommend an accurate response across 236 different countries or regions.

“Australia was very easy - you predict zero cases and you get it right,” she quips. “This is the advantage Australia and New Zealand have of being an island. But you will also have to vaccinate so you don’t get left behind

08/10/2021

Achieve powerful results by listening to your data

07/10/2021

As a Data Analyst, One of the things
that happens is when you work with numbers so much, they start to tell a story, and the ability to look at those numbers and tell that story is what speaks to me. Having always had that
level of numbers, either just that
always attracted to data analytics.

28/09/2021

28/09/2021

28/09/2021

What are some of applications of data analysis?

The application of data analysis in the world today is everywhere.

Every commercial you see today, somebody had to analyze and identify either for the consumer or company, what information they were looking for or wanted to share.

This isn't what something that should be thought of separate or apart from, it is what we do everyday in our lives.

When you're using social media platforms, there are always an analysis going somewhere in system on how you make use of those social media platforms.

Even people monitoring their sugar levels, there always an analysis going on.

Every industrial, every vertical, every function within a given organization can benefit from data analysis, to reach it's optimal. So the applications are universal.

26/09/2021

A retail business should be able to use their vast amounts of data and information in such a way that impacts the business, including:

Tracking inventory

Identifying purchase habits

Detecting user trends and patterns

Recommending purchases

Determining price optimizations

Identifying and stopping fraud
Additionally, you might be looking for daily/monthly sale patterns. Common data segments that you might want to examine include day-over-day, week-over-week, and month-over-month so that you can compare how sales have been to where they were in the same week last year.

24/09/2021

24/09/2021

Businesses need data analysis more than ever. The life and journey of a data analyst, the skills, tasks, and processes they go through in order to tell a story with data so trusted business decisions can be made.

Tools and services are used by data analysts to tell a compelling story through reports.

With data and information as the most strategic asset of a business, the underlying challenge that organizations have today is understanding and using their data to positively affect change within the business.

Businesses continue to struggle to use their data in a meaningful and productive way, which impacts their ability to act.