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What is a Data Lake?

A data lake is a centralized storage repository that stores large amounts of raw data in its original format. This data comes from different sources, such as databases, IoT devices, SaaS data, and log files. The data lake then stores this data in all manners, including structured, semi-structured, and unstructured data, which enables organizations to ingest data without constraints on schema or structure. Having no constraints lets decision-makers easily analyze data, apply machine learning, and gain valuable insights to make data-driven decisions.

Think of any lake you’ve ever been to: It contains water from various sources, such as rain, rivers, snow, and melted ice. A data lake is the same but in data form.

What do we do?

We helped healthcare organizations to Pull data from many systems to overcome the below issues.

Data Quality Issues: Inconsistencies will arise when you have data streaming in from different sources. This is especially true when you can’t filter the type of data coming in. Your data lake may, therefore, end up with data quality issues such as having duplicate records, insufficient data, and data that’s not usable

Scalability Problems: As with any system, without proper scalability mechanisms, data lakes can quickly become overwhelmed when continuously fed large amounts of data, which then results in the system slowing down and causing performance issues.

Disparate Formats: With data lakes, you’ll have all types and formats of data from different sources. Converting all this data into a unified and usable format requires time, effort, specialized tools, and expertise.

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What is a Data Lake?

What do we do?

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