Big Data Dashboards Data Lake IoT 
Jet Global
JULY 2, 2019
To address the flood of data and the needs of enterprise businesses to store, sort, and analyze that data, a new storage solution has evolved: the data lake. What’s in a Data Lake? Data warehouses do a great job of standardizing data from disparate sources for analysis. Taking a Dip.
AWS Big Data
JANUARY 8, 2024
In the subsequent post in our series, we will explore the architectural patterns in building streaming pipelines for real-time BI dashboards, contact center agent, ledger data, personalized real-time recommendation, log analytics, IoT data, Change Data Capture, and real-time marketing data.
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Juice Analytics
MAY 11, 2020
Among all the hot analytics initiatives to choose from (big data, IoT, NLP, data storytelling, cognitive BI, GDPR), plain old reporting is what is considered the most important strategic initiative. But seriously, reporting?
CIO Business Intelligence
JUNE 20, 2022
Designed with controllers, sensors, gateways, real-time dashboards, and custom maintenance roles dubbed ‘Personas,’ Otis One serves roughly one third of Otis’ 2.1 Otis One’s cloud-native platform is built on Microsoft Azure and taps into a Snowflake data lake. based company’s elevators smarter. Rina Leonard, Otis.
AWS Big Data
FEBRUARY 6, 2023
Use case overview Migrating Hadoop workloads to Amazon EMR accelerates big data analytics modernization, increases productivity, and reduces operational cost. Refactoring coupled compute and storage to a decoupling architecture is a modern data solution. Let’s see some real customer use cases in the following sections.
AWS Big Data
FEBRUARY 6, 2023
Amazon QuickSight dashboards showcase the results from the analyzer. With QuickSight, you can visualize YARN log data and conduct analysis against the datasets generated by pre-built dashboard templates and a widget. This step creates datasets on QuickSight dashboards in your AWS target account.
AWS Big Data
MARCH 7, 2023
A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.
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