In this eBook we investigate Big Data, Data Science, Machine Learning, and Analytics. Made studies of these areas and their implications for our jobs and our lives.
Advised about Data Science and Analytics importance for the business and the new Data Scientist career.
Explored different technologies, such as Hadoop System. Showed the Big Data applications that gave rise to the world’s largest data-driven companies.
We saw that we are moving to a new economy, the Data Economy.
Big Data is one of these technologies “Moonshot” that rise and change people’s lives, such as the light bulb invention, smartphone, microcomputer.
Boston Consulting Group predicted that by 2025, software or intelligent robots would substitute a quarter of the world’s jobs.
A study from Oxford University found that half of US jobs are at risk of automation within the next 20 years.
Similar warnings appear in the press, conferences, and Human Resources conferences associated with technology.
It is necessary to assess whether your professional activities will not be a victim of this new era of exponential technologies, Big Data and Digital Transformation.
Perils exist that technology replaces jobs, despite generating others, not in enough quantity to cover the eliminated.
Uber is replacing…
In the age Big Data, Executive Business leaders must think about the data volume and the impact they cause on business.
Have to pay attention to new sources of data from customers, products, services and business operations.
Have to observe the data flow and types, structured, unstructured, such as those from social networks, IoT, emails, and blogs. Data that can count a new history of the company.
This new data history allow identify new opportunities for revenue generation, which is the center of business development.
One fact to consider is to answer the question: Does the company need Big Data…
We saw earlier that:
In Star Trek film, the Data Scientist is Dr. …
A variety of professions and careers have emerged in recent years, directing to the Big Data, Data Science, Analytics, and Machine Learning areas, making this attractive.
Interdisciplinary roles have emerged, which have spawned new Big Data careers, and this process continues as the technology advance.
Is it any wonder that we have new features, new data management tools that end up remodeling careers, improving the labor market and ways of hire.
The most comprehensive career in Big Data is the Data Scientist as we saw earlier.
Other careers for Big Data, Data Science and Analytics are:
1 — Business Analytics
Data Visualization has become a fascinating area in the Big Data era, with the challenge of represent data in large volumes.
The final work of a Data Scientist is to show the results of analyzes, statistical design, computational algorithms, the history that the data want to tell, prophecies and predictions that will happen.
For this, it uses data visualization techniques, interactive and visual ways to represent the information in a format more human, more attractive and visual.
We can say that Data Visualization are ways of representing the data, using images combination, figures, graphics, colors, sounds, graphics and visual elements.
Welcome to the article series “Big Data for Executives and Market Professionals.”
Our goal here is to provide an overview of Big Data. Concepts, technologies, applications, case studies. Data analysis, data insights, machine learning, and practical actions for business results.
The articles alerts Executives and Market Professionals interested in learning about this new area.
Big Data is revolutionizing companies, products, and services, changing markets, and professional careers.
The articles was written to provide an overview of Big Data, Data Science, and Machine Learning.
The Knowledge and content structured in an informative, nontechnical way, for a better understanding and rapid learning.
In the articles Sections, we describe several curiosities on each of the themes. It draws attention and expands your view of Big Data.
Thank you for your interest and wish you a pleasant reading.
Machine Learning (ML) is a commonly used term.
Machine Learning applications have been growing in many areas of human activities such as health, education, entertainment, fraud and industry.
Machine Learning and Big Data complement each other, with large volumes of data being used to “train” or “educate” intelligent application, which goes over time learning.
Let’s describe Machine Learning at a conceptual level so we can visualize its application with Big Data and practical market applications.
Data Science is the practice of collecting, organizing, and optimizing complex data, discovering variable relationships and anomalies, and developing applications that transform data into insights.
Data Analytics Tools (credits pixabay)
Data analysis tools are in high demand.
Data become an asset to the company. It only has value if possible to extract knowledge and insights.
There are many Data Analysis tools.
Ranging from the most used programming languages such as Python and R, tools oriented towards statistical or mathematical solutions, tools that have evolved from BI, commercial tools from big companies such as Amazon, Microsoft, Google, IBM, until those who were born in the era of Big Data.
Of the dozens of existing tools, we list here some of them, used in Analytics, Data Science…
Big Data can bring a personalized experience to millions of users, understand what motivates customers, delay production lines, analyze genomes for cancer research, and evolve into astronomy and physics.
To gain insight into data, is necessary to apply analytical methods to your data treatment, a practice known as “Data Science.”
Analytical Methods aim at guessing the future, developing prophecies, predictions, and this we call “Predictive Analytics.”
The term “Analytics” or “Data Analytics” is more used than Big Data considering that companies do data analysis in various areas such as finance, marketing and business.
Business Intelligence performs data analysis but does…