Data Visualization of Healthcare expense by country using Web Scraping

As the world is facing the worst pandemic ever, I was just looking at how much countries spend on their healthcare infrastructure. So, I thought of doing a data visualization of the medical expenses of several countries. My search led to this article, which has data from many countries for the year 2016. I did not found any authentic source for the latest year. So, we’ll continue with 2016.

#data-visualization #web-scraping #web-development #programming #python

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Data Visualization of Healthcare expense by country using Web Scraping
Ray  Patel

Ray Patel

1623262740

Cloud Based Web Scraping for Big Data Applications 

Have you ever wondered how companies started to maintain and store big data? Well, flash drives were only prevalent at the start of the millennium. But with the advancement of the internet and technology, the big data analytics industry is projected to reach $103 billion by 2027, according to** Statista**.

As the need to store big data and access instantly increases at an alarming rate, scraping and web crawling technologies are becoming more and more useful. Today, companies mainly use web scraping technology to regulate price, calculate the consumer satisfaction index, and assess its intelligence. Read on to find the uses of cloud-based web scraping for big data apps.

What is Web Scraping?

How Cloud-Based Web Scraping Benefits an Organisation?

#data-analytics #web-scraping #big-data #cloud based web scraping for big data applications #big data applications #cloud based web scraping

 iOS App Dev

iOS App Dev

1620466520

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Data Visualization of Healthcare expense by country using Web Scraping

As the world is facing the worst pandemic ever, I was just looking at how much countries spend on their healthcare infrastructure. So, I thought of doing a data visualization of the medical expenses of several countries. My search led to this article, which has data from many countries for the year 2016. I did not found any authentic source for the latest year. So, we’ll continue with 2016.

#data-visualization #web-scraping #web-development #programming #python

Sid  Schuppe

Sid Schuppe

1617988080

How To Blend Data in Google Data Studio For Better Data Analysis

Using data to inform decisions is essential to product management, or anything really. And thankfully, we aren’t short of it. Any online application generates an abundance of data and it’s up to us to collect it and then make sense of it.

Google Data Studio helps us understand the meaning behind data, enabling us to build beautiful visualizations and dashboards that transform data into stories. If it wasn’t already, data literacy is as much a fundamental skill as learning to read or write. Or it certainly will be.

Nothing is more powerful than data democracy, where anyone in your organization can regularly make decisions informed with data. As part of enabling this, we need to be able to visualize data in a way that brings it to life and makes it more accessible. I’ve recently been learning how to do this and wanted to share some of the cool ways you can do this in Google Data Studio.

#google-data-studio #blending-data #dashboard #data-visualization #creating-visualizations #how-to-visualize-data #data-analysis #data-visualisation

 iOS App Dev

iOS App Dev

1622516462

What is Big Data in Healthcare and How is it Used?

The pandemic is having an enormous impact on the healthcare sector. Between overwhelming hospitalization rates, intensifying cybersecurity threats, and an aggravating number of mental illnesses due to strict lockdown measures, hospitals are desperately searching for help. Big data in healthcare seems like a viable solution. It can proactively provide meaningful, up-to-date information enabling clinics to address pressing issues and prepare for what’s coming.

Hospitals are increasingly turning to big data development service providers to make sense of their operational data. According to Healthcare Weekly, the global big data market in the healthcare industry is expected to reach $34.3 billion by 2022, growing at a CAGR of 22.1%.

So, what is the role of big data analytics in healthcare? Which challenges to expect? And how to set yourself up for success?

How Big Data Can Help Solve Healthcare Problems

Big data has several accepted definitions. Here are two popular ones:

Douglas Laney’s definition. Laney is a former Chief Data Officer at Gartner. He states that big data is characterized by 3 Vs: volume, velocity, and variety. The volume stands for large amounts of data. Velocity refers to the speed of collecting data and making it accessible, while variety indicates the different types of data, such as text, video, logs, audio, etc.McKinsey’s definition. The renowned consulting firm defines big data as datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze.

According to an IDC report, the volume of big data is expected to reach 175 Zettabytes by 2025. To put it in perspective, it will take 1.8 billion years to download this amount of data with the average internet speed available nowadays.

#big-data #big-data-analytics #healthcare-and-big-data #healthcare-tech #medical-software-development #healthcare-software #big-data-processing #healthcare-software-solution