Ian  Robinson

Ian Robinson

1622299140

The Top 5 Big Data Applications in the Healthcare Industry

Big data has leveraging potential to revolutionize the healthcare sector in many ways. Below are the top 5 big data applications to transform healthcare.

In this modern era of leveraging technology, the enhancement of healthcare sectors is crucial especially during the pandemic of COVID-19. Technological advancements can either make or break the future of healthcare and can control the second wave of coronavirus. One method which can be acquired to make healthcare more efficient, accurate, and affordable is by utilizing big data.

Big data has completely revolutionized the way data is analyzed, managed, and leveraged across numerous industries. Noticeable sectors where data analytics is making prominent changes in healthcare. It is estimated that the global big data in the healthcare market will tend to reach $34.27 billion by the year 2022 at a CAGR of 22.07%. Moreover, big data in the healthcare market is expected to bypass the figure of $68.03 billion by the year 2024.

There is no surprise in saying that big data analytics in healthcare has a life-saving yet positive outcome. Essentially big data refers to an extensive amount of information that is produced by the digitization of everything, that is synthesized and analyzed using certain technologies. Particular health data of population is utilized for the prevention of epidemics, cut down cost, cure disease and so on. Doctors want to develop a better understanding as much as they can and as early as possible about their patients to detect the warning signs of some serious illness as that occurs.

Let us dive deeper into big data challenges, applications, and its bright future in the healthcare sector that demonstrate how an analytical approach can enhance patient care, processes, and can ultimately save lives.

#big data #analysis #healthcare app development #big data algorithms #ai algorithm

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The Top 5 Big Data Applications in the Healthcare Industry
Gerhard  Brink

Gerhard Brink

1624692167

Top 10 Big Data Tools for 2021!

In today’s tech world, data is everything. As the focus on data grows, it keeps multiplying by leaps and bounds each day. If earlier mounds of data were talked about in kilobytes and megabytes, today terabytes have become the base unit for organizational data. This coming in of big data has transformed paradigms of data storage, processing, and analytics.

Instead of only gathering and storing information that can offer crucial insights to meet short-term goals, an increasing number of enterprises are storing much larger amounts of data gathered from multiple resources across business processes. However, all this data is meaningless on its own. It can add value only when it is processed and analyzed the right way to draw point insights that can improve decision-making.

Processing and analyzing big data is not an easy task. If not handled correctly, big data can turn into an obstacle rather than an effective solution for businesses. Effective handling of big data management  requires to use of tools that can steer you toward tangible, substantial results. For that, you need a set of great big data tools that will not only solve this problem but also help you in producing substantial results.

Data storage tools, warehouses, and data lakes all play a crucial role in helping companies store and sort vast amounts of information. However, the true power of big data lies in its analytics. There are a host of big data tools in the market today to aid a business’ journey from gathering data to storing, processing, analyzing, and reporting it. Let’s take a closer look at some of the top big data tools that can help you inch closer to your goal of establishing data-driven decision-making and workflow processes.

Apache Hadoop

Apache Spark

Flink

Apache Storm

Apache Cassandra

#big data #big data tools #big data management #big data tool #top 10 big data tools for 2021! #top-big-data-tool

Siphiwe  Nair

Siphiwe Nair

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

Lisa joly

Lisa joly

1624090500

Top 5 Big Data Applications in Banking & Insurance

By nature, the banking, financial services, and insurance (BFSI) sector have always been data-driven. However, today, institutions in the BFSI sector are increasingly striving to adopt a full-fledged data-driven approach that can only be possible with Big Data technologies. With Big Data Analytics, companies in the BFSI sector can not only grow their business but also work towards increasing customer satisfaction.

Although data analytics has been an integral part of the BFSI sector, nowadays, companies in this sector are steering towards Big Data Analytics. The fundamental question that stakeholders ask before adopting Big Data is –

How can Big Data enhance our business and solve our problems?

With Big Data, companies can access valuable and accurate insights from large datasets, which gives them a competitive advantage over their rivals. Big Data the potential to bring many benefits to the table, including increased levels of customer insight and engagement, improved market trading analysis, and enhanced fraud detection and prevention, among other things. The most noteworthy contribution of Big Data to the BFSI sector is ‘real-time evaluation’ that allows banks and financial institutions to track and monitor customer behavior in real-time and offer prompt solutions accordingly. As the quality of services improves and delivery time reduces, it will provide a significant boost to customer satisfaction while also improving the overall profitability of the organization.

Big Data allows BFSI institutions to obtain a comprehensive understanding of customers, products/services, markets, industry regulations, competitors, and advertising channels. The most significant areas of application of Big Data in the BFSI industry are:

#big data #top 5 big data applications in banking & insurance #banks #big data applications #major applications #good

Silly mistakes that can cost ‘Big’ in Big Data Analytics

Big Data has played a major role in defining the expansion of businesses of all kinds as it helps the companies to understand their audience and devise their business techniques in accordance with the requirement.

The importance of ‘Data’ has been spoken very highly in the modern-day business. Thus, while using big data analysis, the companies must keep away from these minor mistakes otherwise it could have a major impact on their performances. Big Data analysis can be the silver bullet that can answer your questions and help your business to scale newer heights.

Read More: Silly mistakes that can cost ‘Big’ in Big Data Analytics

#top big data analytics companies #best big data service providers #big data for business #big data technology #big data mistakes #big data analytics

Ian  Robinson

Ian Robinson

1624399200

Top 10 Big Data Tools for Data Management and Analytics

Introduction to Big Data

What exactly is Big Data? Big Data is nothing but large and complex data sets, which can be both structured and unstructured. Its concept encompasses the infrastructures, technologies, and Big Data Tools created to manage this large amount of information.

To fulfill the need to achieve high-performance, Big Data Analytics tools play a vital role. Further, various Big Data tools and frameworks are responsible for retrieving meaningful information from a huge set of data.

List of Big Data Tools & Frameworks

The most important as well as popular Big Data Analytics Open Source Tools which are used in 2020 are as follows:

  1. Big Data Framework
  2. Data Storage Tools
  3. Data Visualization Tools
  4. Big Data Processing Tools
  5. Data Preprocessing Tools
  6. Data Wrangling Tools
  7. Big Data Testing Tools
  8. Data Governance Tools
  9. Security Management Tools
  10. Real-Time Data Streaming Tools

#big data engineering #top 10 big data tools for data management and analytics #big data tools for data management and analytics #tools for data management #analytics #top big data tools for data management and analytics