In the current times, the healthcare industry is one of the leading producers of data. As the COVID-19 pandemic continues to cause seismic shifts worldwide, healthcare providers realize the potential of adopting data analytics tools. However, to reinforce the data analytics foundation across the care continuum, it is vital to have the correct data at the right time in the right format.
Already, healthcare organizations have begun to embrace a single data platform rather than multiple platforms. A single platform ensures easy access and on-demand analysis of health data. So, the concept of a data lake attracts healthcare facilities as it gives a real-time, in-depth analysis of diversified data sets. There are various data lake tools and frameworks, but Microsoft Azure Data Lake is wreaking havoc in the healthcare industry.
Microsoft’s Azure is one of the leading platforms for data lakes. It includes all the capabilities required to consolidate, catalog and centralize your medical big data. In this blog post, you will get to know how Azure data lake is growing in popularity within the medical field.
Biggest challenges in building a data lake
While the healthcare industry uncovers a range of benefits from big data, you can face new challenges in building and managing a data lake. The three biggest challenges in building a data lake are:
Ingesting multi-dimensional data from disparate sources
One of the biggest and common issues is collecting and ingesting diversified health data from disparate data sources. A large amount of data ingested from multiple sources may lead to data swamp.
Maintaining data quality and reliability
Data quality and reliability issues can easily go undetected. So, another challenge is to maintain the quality of data and to make data lakes reliable. High-quality, consistent data forms the backbone of building a reliable data lake.
Access control and security
In the digital age, breaches of patient data, health records and personal identities have significantly increased. So, another problem is to secure a data lake with a different access control model like role-based and view-based.
The role of Azure Data Lake in the healthcare sector
The rise of connected health devices, ML-based machines and healthcare big data is taking the medical field by storm. Healthcare data is growing in number across the globe. For instance, a single full-body scan generates around 10GB of raw image data into a healthcare institution’s data storage. So, to store and manage a large amount of data, healthcare providers need a robust data storage platform.
Microsoft Azure Data Lake can store, search, share and analyze healthcare data of any size, shape, or speed, making life easier. It also enables you to analyze health data in real-time without any pre-defined structure or third-party assistance. Azure Data Lake is ideal for supporting new approaches. For instance, to ingest, collect and connect Electronic Health Records (EHR) at a single place, like Precision Medicine. There are mainly three components of Azure Data Lake:
1. Azure Data Lake Store
2. Azure HD Insights and
3. Azure Data Lake Analytics
Healthcare organizations must utilize the Azure Data Lake platform for two main reasons – enhanced agility and convenience for data analysis. Not only this, but it also helps to streamline health data management processes. It will enable you to minimize costs while maximizing the ROI on data management. With the help of ADL, modern medical institutions can fulfill the promise of faster and better patient care.
Azure data lake use cases in healthcare
Psychographic prescriptive modeling: The tool can help to get considerable insights into a patient’s additional disease risk factors. You can do it by collecting psychographic data of patients and feeding it to Azure Data Lake.
Genomic data analytics: The tool will help health insurance providers to manage a massive amount of genetic data. By using Azure Data Lake, insurers can make data management easier, enhance agility, data security and access to scalable storage.
Predictive medical costs: The tool can assist to analyze and predict healthcare expenses too. Based on the structured and unstructured data in the Azure Data Lake, you can have a predictive medical cost model.
Improved clinical trials: Based on the data available in ADL, analysis of clinical trials can assist in discovering drug combinations with enhanced improvements.
360-degree view of patients’ health’ report: The tool can help you predict disease outbreaks, develop cures for them, and identify preventative care.
Transform the healthcare journey
Microsoft’s Azure Data Lake can solve a myriad of problems related to massive amounts of healthcare data – structured or unstructured. But medical institutions must properly build and manage the data lake solution. To build a modern clinical health data lake using Microsoft Azure, get in touch with our data experts. Our adept team will also assist you to know how to make righteous use of your massively large clinical or healthcare data.