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How Big Data Analytics Address COVID-19 Concern in Healthcare Industry?

big data analytics and covid

The Coronavirus Pandemic has spurred interest in big data to track the spread of the fast-moving pathogen and to plan disease prevention efforts. But the urgent need to contain the outbreak shouldn’t cloud thinking about big data’s potential to do more harm than good. Here is how big data analytics address COVID-19 concern in the healthcare industry.

Big data’s blind spots could lead public health authorities astray, diverting critical resources from proven containment methods such as aggressive testing.

They could also lead to draconian restrictions that disproportionately impact the rights of those under- or misrepresented by the data. In Israel, the government’s cell phone location-tracking program has caused complaints that the authorities are erroneously confining people to their homes based on inaccurate location data.

While the capacity of big data to help curb the coronavirus outbreak is, at best, uncertain, its risks to privacy are immense. Governments and companies have cited the anonymization of personal data as a key privacy safeguard, but multiple studies show that this may only delay rather than prevent the person’s re-identification.

Location data is particularly vulnerable since it can be combined with public and private records to create an intricate and revealing map of a person’s movements, associations, and activities.

Impact of Big Data Analytics in Healthcare on COVID-19 Outbreak

COVID-19 has arrived with consequences that are grave and unsettling. Big Data lies at the heart of efforts to comprehend and forecast the impact that Coronavirus will have on all of us.

The near real-time COVID-19 trackers that continuously pull data from sources around the world are helping healthcare workers, scientists, epidemiologists and policymakers aggregate and synthesize incident data on a global basis.

There has been some interesting data resulting from GPS analyses of population movement by region, city, etc., which ultimately helps provide a view of the population’s compliance — or lack of compliance — with social-distancing mandates.

There are many opportunities to make the use of Big Data more impactful in situations like these as a society and as an industry, though no one yet been able to effectively leverage the power of Big Data in search of a cure.

Ideas such as creating large scale COVID-19 Real World Evidence (RWE) studies that pull data from a variety of real-world sources — including patients now be treated in the hospital setting — could help accelerate the development of treatments in a more patient-centric and patient-friendly way.

Global Big Data Analytics in Healthcare Industry Landscape

According to Goldstein Market Intelligence research, the market size of big data analytics in the healthcare industry was valued at USD 16.90 billion in 2017 and is projected to reach USD 68.20 billion by 2025 and is expected to expand at a CAGR of 18.6% over the forecast period.

Based on types of analytics type, the descriptive analytics segment is anticipated to account for the largest share of the big data healthcare analytics market and continue to dominate the big data analytics in the healthcare industry during the forecast period.

Based on geography, North America is expected to dominate the market followed by Europe during the forecast period, due to a rise in advancements in IoT and an increase in the demand for analytical models on patient information for better service delivery, government policies.

Substantial Upsurge in Demand for Financial Analytics in Healthcare is Driving The Global Big Data Analytics in Healthcare Industry

Every day, people working with various organizations around the world are generating a massive amount of data. The term “digital universe� quantitatively defines such massive amounts of data created, replicated, and consumed in a single year.

The digital universe in 2017 expanded to about 16,000 EB or 16 zettabytes (ZB) and would expand to 40,000 EB by the year 2020.

National Institutes of Health (NIH) recently announced the “All of Us� initiative that aims to collect one million or more patient’s data such as EHR, including medical imaging, socio-behavioral, and environmental data over the next few years. EHRs have introduced many advantages in handling modern healthcare related data.

The advantage of EHRs is that healthcare professionals have an improved access to the entire medical history of a patient. The information includes medical diagnoses, prescriptions, data related to known allergies, demographics, clinical narratives, and the results obtained from various laboratory tests.

Major factors driving the growth of big data analytics in the healthcare sector include substantial upsurge in demand for financial analytics. There is an increased demand for discovering structured and unstructured data existing in the healthcare industry, declining costs, and accessibility of big data software and services. There is also augmented adoption of novel technologies for data analytics in healthcare industry transformations, worldwide.

Big Data Analytics have already made a significant impact on grounds related to healthcare: medical diagnosis from imaging data in medicine, quantifying lifestyle data in the fitness industry, to mention a few.

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6 Skills You Need to Become a Data Analyst

become data analyst

Data analyst is the process in which the judgment, refining, changing, and modeling data takes place with the aim of making a better conclusion. Data analysis takes part in an important role, it helps in generating scientific conclusions and also increases the regulations in an organization. Here are six skills you need to become a data analyst.

Data-Driven Business Strategies

Today, with the deepening of the concept of data operation, more and more companies are aware of the value of data-driven business strategies and emphasize the participation of all employees in data operations. Developing the ability to analyze data is also a future trend.

A data analyst is someone who accumulates data, processes, and performs analysis of data. He or she can interpret numbers and data into simple English in order to help organizations and companies understand how to make better business decisions.

At its core, data analysis means taking a business question or need and turning it into a data question. Then, you’ll need to transform and analyze data to extract an answer to that question.

Companies of today realize how data-driven strategy is important to them and they are in need of talented individuals who can provide insights into a constant stream of collected information.

Types of Data Analysts

  • Finance
  • Data assurance
  • Business Intelligence
  • Marketing
  • Sales

The types of data analyst listed above are some of the most challenging fields which require a data analyst in their management.

Here are 6 skills you need to become a data analyst.

1. MATHEMATICAL SKILLS

Mathematical skills are important for making a profession in data analysis, as you have to play with numbers and figures all through the day. Necessary mathematics skills include:

*One should be good at calculations

*Measuring and analyzing data

*Having the ability to organize information

*One should know how to schedule and budget

Mathematical skills help in having better problem-solving skills — and also helps in financing our individual businesses.

2. ANALYTICAL SKILLS

As it is called, It is clear that analytical skills are the huge significance of data analysis. These skills include assembling, sorting, and analyzing all kinds of raw data in particular. It also helps you to view provocation or situation from a different angle. Hence, If you want to be a professional data analyst then you need to widen your analytical skills and thinking. Analytical skills help in viewing a challenge or situation from different perspectives. It is one of the most important and efficient parts of the skill you need to become a data analyst.

3. TECHNICAL SKILLS

Good computer and technical skills are very important. The main knowledge of statistics is quite helpful as well as producing languages like python or Mat Lab, and analytical languages like R and SAS are very favorable to know as a data analyst.

The more language you know, the faster and better for you to get your dream job. Examples of technical skills you need to know are:

  • Programming languages.
  • Common operating systems.
  • Software proficiency.
  • Technical writing.

4. DETAILS SKILLS

Data analyst is all about details, It helps a data analyst to be able to find and see any basic unseen errors and links, that is especially important at the point of solving problems and making decisions.

5. BUSINESS SKILLS

Aside from the technical skills, there are some business skills that one should acquire to function as a Data analyst. Some of which are:

Communication Skills:

As a data analyst, you are expected to work with different sets of people in your team which makes your communication a really important part of your job. Working well together as a team for the benefit of your organization is also one of your main responsibilities and skill.

You should be able to communicate effectively with the teammates to prepare, present, and explain data. Communication is key in collaborating with your colleagues. For example, in a kickoff meeting with business stakeholders, careful listening skills are needed to understand the analyses they require.

Similarly, during your project, you may need to be able to explain a complex topic to non-technical teammates.

Time Management and Organizational Skills:

As it is expected of you to work with different people in your team. You should be able to manage your time including your responsibilities, as well as meet your deadlines.

Decision-making and Problem-solving:

These skills are the bottom line of data analysis. The main job of a data analyst is to give the right information for decision-making and problem-solving process. Which is why it occurs to be a perfect skill required to be a data analyst.

You might need to research a quirk of some software or coding language that you’re using. Your company might have resource constraints that force you to be innovative in how you approach a problem.

The data you’re using might be incomplete. Or you might need to perform some “good enoughâ€� analysis to meet a looming deadline.

6. DOMAIN KNOWLEDGE

Domain knowledge is understanding things that are specific to the particular industry and company that you work for. For example, if you’re working for a company with an online store, you might need to understand the nuances of e-commerce. In contrast, if you’re analyzing data about mechanical systems, you might need to understand those systems and how they work.

Domain knowledge changes from industry to industry, so you may find yourself needing to research and learn quickly. No matter where you work if you don’t understand what you’re analyzing it’s going to be difficult to do it effectively, making domain knowledge a key data analyst skill.

Remember that Domain knowledge is certainly something that you can learn on the job, but if you know a specific industry or area you’d like to work in, building as much understanding as you can upfront will make you a more attractive job applicant and a more effective employee once you do get the job.

Once you have the skills mentioned above — you can use them to attract attention to yourself so as to get your dream job. These are the criteria you need for the data analyst skills checklist.

Academic Background

A bachelor’s degree is often necessary, not all the time though. To work as a data analyst you need to acquire a degree in any of these Science courses.

  • Economics
  • Business information systems
  • Mathematics
  • Statistics
  • Computer science

As much as the above degrees are important for your success — what matters the most are the skills that you possess. Right now during the COVID-19 problems may be the time for you to upgrade yourself and your skills.

Conclusion

Data analysis is speedily growing field and skilled data analysts are huge in demand throughout the country, in every industry. This means that you would find many opportunities only if you are exceptional and show your excellent data analytic skills.

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