Remove Data Lake Remove Reporting Remove Structured Data
article thumbnail

Understanding the Differences Between Data Lakes and Data Warehouses

Smart Data Collective

Data lakes and data warehouses are probably the two most widely used structures for storing data. Data Warehouses and Data Lakes in a Nutshell. A data warehouse is used as a central storage space for large amounts of structured data coming from various sources.

Data Lake 140
article thumbnail

Data Lakes on Cloud & it’s Usage in Healthcare

BizAcuity

Data lakes are centralized repositories that can store all structured and unstructured data at any desired scale. The power of the data lake lies in the fact that it often is a cost-effective way to store data. Deploying Data Lakes in the cloud. Best practices to build a Data Lake.

Data Lake 102
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Complexity Drives Costs: A Look Inside BYOD and Azure Data Lakes

Jet Global

Reporting will change in D365 F&SCM, and those changes could significantly increase complexity and total cost of ownership. To enhance security, Microsoft has decided to restrict that kind of direct database access in D365 F&SCM and replace it with an abstraction layer comprised of something called “data entities”.

article thumbnail

Navigating Data Entities, BYOD, and Data Lakes in Microsoft Dynamics

Jet Global

Consultants and developers familiar with the AX data model could query the database using any number of different tools, including a myriad of different report writers. The SQL query language used to extract data for reporting could also potentially be used to insert, update, or delete records from the database.

article thumbnail

Implement slowly changing dimensions in a data lake using AWS Glue and Delta

AWS Big Data

As organizations across the globe are modernizing their data platforms with data lakes on Amazon Simple Storage Service (Amazon S3), handling SCDs in data lakes can be challenging.

Data Lake 101
article thumbnail

How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

In the following section, two use cases demonstrate how the data mesh is established with Amazon DataZone to better facilitate machine learning for an IoT-based digital twin and BI dashboards and reporting using Tableau. This agility accelerates EUROGATEs insight generation, keeping decision-making aligned with current data.

IoT 111
article thumbnail

Building a Beautiful Data Lakehouse

CIO Business Intelligence

As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio.

Data Lake 119