Big Data
Things to be comprehend in analytical approach (Descriptive Analysis, Diagnostic Analysis, Predictive analytics, trend Analysis, prescriptive analysis, Cognitive (sensation, intuition, thinking, and feeling) analysis) using the large body of information named Big data.
Big data, point’s to data sets that are in massive volume or complex to be dealt with the normal data-processing solutions. Please note that only airplanes generate enormous volumes of data, on the order of 1,000 gigabytes for transatlantic flights, or GPS smartphone applications, social media, net flix, amazon, uber, health care systems, satellite images, streaming data, huge data sets etc., producing tremendous volume of unstructured data, structured data, semi structured data in every day.
Don’t forget AI and data infrastructure contributed over $2.3 trillion to U.S. GDP growth (source: McKinsey, World Economic Forum estimates).
BIG Data Processing in Healthcare: Personalized Medicine:
By analyzing genetic, lifestyle, and medical history data, healthcare providers can tailor treatments to individual patients, leading to more effective care. This includes understanding how different patients respond to medications, identifying potential side effects, and optimizing treatment plans.
Big Data Analytic tools: Big data analytics tools encompass a wide array of software and platforms designed to manage, analyze, and visualize large volumes of data. These tools are crucial for extracting valuable insights from big data and making informed decisions. Popular tools include Apache Hadoop, Apache Spark, Tableau, and Power BI.
Big Data Architect for Health care: A Big Data Architect in healthcare designs and implements data solutions to manage and analyze large amounts of patient data, enabling better decision-making and improved patient outcomes. They focus on optimizing data collection, storage, analysis, and utilization while ensuring scalability, security, and interoperability. This role is crucial for leveraging big data to improve healthcare practices, streamline operations, and advance medical research. Key Responsibilities of a Big Data Architect in Healthcare:
Data Architecture Design: Developing and implementing data architectures that meet the specific needs of healthcare organizations, considering factors like data volume, variety, velocity, and veracity.
Streamlined Operations: Big data can optimize workflows, reduce costs, and improve efficiency in areas like hospital admissions, medication management, and resource allocation.
Telemedicine and Remote Monitoring: Using data from wearable devices and other sensors to monitor patients remotely and provide timely interventions.