Gartner, the information technology and advisory company, has implied that there is a shift towards composite approaches when it comes to data management, as organizations are looking for ways to solve complex issues with a mix of traditional and alternative deployments.

Modern-day healthcare big data analytics need a new approach to advanced, flexible data management for engaging patients, keeping track of organizations, and work on population health.

So, the healthcare industry is posed with the question, whether they need a data lake as a part of their architecture. It is at the top of the mind of healthcare professionals who are challenged to work on the medical outcomes for their patients.

In this guide, we will dig deeper into the role of Data Lake healthcare to learn if it solves its big data problem.

What is a Data Lake?

A central storage repository holding big data from different sources in a granular and raw format is called a Data Lake. It is capable of storing unstructured, semi-structured, and structured data. So, you can save data in a flexible format to use in the future. While storing data, Data Lake associates it with metadata tags and identifiers for faster data retrieval.

The term ‘Data Lake’ is coined by James Dixon, CTO of Pentaho. Configuration of data lakes is mostly done on a cluster of low-priced and scalable commodity hardware. This let’s data be dumped in the lake to be used later if required, without having to bother about storage capacity.

Data Warehouse is another form of data storage. Based on the requirements, a healthcare organization might require both Data Lake and Data Warehouse since they serve different requirements.

A Data Warehouse is optimized for analyzing relational data that are received from a line of business applications and transactional systems. The schema and data structure are defined in advance for optimizing fast SQL queries, where the outcome is used for analysis and operational reporting. Data is cleaned, tweaked, and transformed making it work like a source that a user can trust.

What are the Advantages of Using Data Lake?

The primary benefit of Data Lake is that you can store all data in a single place at a low cost. However, how can healthcare organizations benefit from this, let’s find out.

Data is Available 24/7

Data Lake will provide data access to all the authorized employees, irrespective of their position in the organization. So, it makes room for the democratization of data. It makes sure that data isn’t just available to the managers but also to the employees. Thus, employees can use them in important meetings or other requirements.

Cheap Scalability

Another benefit of Data Lake healthcare organization is its ability to maintain a large amount of data at a small price. When organizations look for solutions to store data, the primary factor they take into account is storage cost. Data Lake offers sound financial values.

Legitimately Hordes Data

Since using Data Lake is cheap and provides a large variation in data types, organizations get the chance of hoarding their data. It means that if a certain data isn’t of any value; a company can easily store it for future use. Data Lakes feeds data in a native format. This means it can be added and stored over time for future analysis.

Makes Room for Future Technological Changes

In a couple of years, there have been dynamic changes in the field of data technology. This is a reason data plays a significant role in every business. It gives healthcare organizations the opportunity to store data in the native format prior to being changed to a structured database to use in the future. This makes it easier to pull out any data to a required system if required.

Supports SQL and Other Languages

Even though conventional data warehouse technology supports SQL those are just good for simple data analytics. Data Lake is used in advanced cases as it provides various. It has features that can easily handle advanced requirements.

Versatile and Scalable

Unlike a conventional data warehouse, Data Lake provides scalability at a cheaper price. It uses Hadoop, a scalable tool that leverages the HDFS storage for managing the increasing amount of data and accommodates data growth. Also, it is versatile. So, organizations can use it to store unstructured and structured data from various sources.

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Challenges of Data in Healthcare

There are various challenges when it comes to big data analytics in the healthcare industry. It includes data integrity, security, and visualization issues.

Fragmented Data

Healthcare data is secured from various sources and in different formats. Data collection is also fragmented. So, integration and extraction can be a real challenge. Payers, providers, employers, public health specialists, and patients, all collect data. However, no effort is made to unify the details. This might result in incomplete and inaccurate healthcare profiles with little understanding of the patient’s treatment journey.

Ever-Changing Data

Physicians and patients, move, change professions, change names, retire, and pass away. The payer organization might also relocate. Furthermore, the introduction of new drugs, treatments, and personalized care models can change data security. So, it can be a challenge to keep data clean, updated, and complete.

Security and Privacy Regulations

Maintaining trust is the basis of building an effective healthcare ecosystem. Data security is crucial to the healthcare industry since the privacy of patients depends on HIPAA2 compliance. Poor data strategy and quality keep organizations from catering to the new regulatory needs. Till the time data security and privacy issues are completely addressed, improving the healthcare facilities is going to be a tough challeng

How can Data Lake Help in Solving the Challenges?

Data Lake has the ability to harness more data from different sources in less time. This empowers users to analyze and collaborate in various ways, leading to faster and better decision-making.

Data Lakes Delivers Tremendous Value to the Healthcare Industry

A Data Lake enables prescriptive and predictive analytics that is important for supporting healthcare use cases or initiatives. It offers strong data architecture with a uniform location for helping with the reduction of silos across the healthcare industry. Data Lakes enables cross-data analysis and integrates all internal data and external data sources to mine and analyze.

The reliable and flexible platform provides a myriad of new opportunities for finding correlations and trends, helping healthcare providers to develop a continuous data-driven learning environment.

Why Is This the Best Time for Healthcare Organizations to Adopt Data Lake?

This is the generation of information. Everything has gone digital and has put information at our fingertips. With both consumers and patients of healthcare, our demand for preventive wellness and disease management, and diagnosis speed, are changing.

With new possibilities, arise new opportunities for closing the gaping hole between reality and the promise of big data analytics and increase efficiencies for improving patient care. This can be done with the help of Data Lakes.

What Healthcare should Do for a Faster Adoption of Data?

To deploy Data Lake, three prerequisites have to be identified:

Data Lakes are the best workload to be deployed in the cloud. This is because the cloud offers scalability, performance, availability, and reliability at a diverse set of analytic engines. ESG research discovered that 39% of respondents take Cloud based Data Lake as the main deployment for analytics, 43% for Spark, and 41% for data warehouses.

Cloud based Data is advantageous because it offers better security, better availability, and more frequent functionality updates.

How does ResolveData Help with Building Data Lakes for the Healthcare Industry?

Using Data Lake applications and analytics from data actuaries and scientists, data can be consumed and leveraged by providers and payers in different ways in Data Lake. With an increase of data in the healthcare industry, flexible and cost-effective solutions, like Data Lake can bring about a significant difference. And, ResolveData can help your healthcare organization to integrate and deploy Data Lake in your system, smoothly. We use an intelligent data management system to help you outperform your competitors and provide improved healthcare.

ResolveData believes in simplifying and accelerating decision-making. With the help of Data Lake, your organization can simplify and drive healthcare business for delivering impact.

Can Data Lake Solve Healthcare’s Big Data Problem?