Health care will spend 18 billion in spending on deep learning
BY: FAWAD KHAN- Project Management Consultant @KeyMetricsXP
As digitization sweeps across every horizontal and vertical market, data has become the new corporate currency. Data is everywhere and growing faster than ever. When data is managed properly, it becomes a competitive advantage for any organization; but without interpretation, it’s only a collection of facts. Various analytical techniques have transformed data into valuable information for organizations to identify trends and metrics which would otherwise be lost or disregarded. To manage the tremendous volume of big data, organizations have been investing heavily in analytical techniques such as machine learning, data mining, and natural language processing. Following a report published by International Data Corporation, big data is expected to grow faster in healthcare than any other sector; and by 2024, the public and private investments in health analytics will be worth more than $68 billion globally. The driving forces contributing to the growth are accredited to the adoption of IoT enabled devices, electronic record systems, cloud analytics, government regulations, and advancements to data management techniques. North America is anticipated to hold the largest market share.
The affect on the data science is extensive and in demand. Business intelligence software uses charting and predictive modeling to support better business decision making. AI is still a relatively new technology in the healthcare, but the demands of big data analytics continues to increase. From provider care to clinical research, pharmaceutical R&R and insurance, AI is revolutionizing how health organizations work to reduce spending and improve patient care. A report from HealthITAnalytics states the health sector will be one of the top players in the global market to spend $18 billion on deep learning technologies to analyze images, extract meaning from unstructured data, and support business initiatives. Deep learning, one of the most promising branches of AI, will see a 42% increase in compound annual growth rate.
As big data continues to get bigger, organizations will have to devise ever-more innovative solutions to manage data. An estimated 80% of companies are investing in AI. Positions like machine learning engineer, data engineer, and data scientist are among the most in-demand AI jobs as companies search for candidates to help bring AI to their workplace. According to Indeed, the demand for AI jobs grew 29%. These jobs include:
Machine Learning Engineers: responsible for building and managing platforms for machine learning projects. Annual median salary of $141,439
Data Scientists: possess a deep understanding of statistics and algorithms, programming and communication skills. Annual median salary of $120,655.
Big Data Engineers: responsible for developing the ecosystem that enables business systems to communicate and gather data. Most positions require a Ph.D. in mathematics, or computer science. Annual median salary of $130,541.
Business Intelligence Developers: key players to enable efficiency and profitability of a business project. Annual median salary of $90,671.
Data Warehouse Architect: responsible for designing data warehouse solutions and working with conventional data warehouse technologies to come up with plans that best support a business. Annual median salary of $133,764.