Remove Data Analytics Remove IoT Remove Visualization
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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

Their terminal operations rely heavily on seamless data flows and the management of vast volumes of data. Recently, EUROGATE has developed a digital twin for its container terminal Hamburg (CTH), generating millions of data points every second from Internet of Things (IoT)devices attached to its container handling equipment (CHE).

IoT 111
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The role of IoT in shaping smart cities

CIO Business Intelligence

Cities are embracing smart city initiatives to address these challenges, leveraging the Internet of Things (IoT) as the cornerstone for data-driven decision making and optimized urban operations. According to IDC, the IoT market in the Middle East and Africa is set to surpass $30.2 Popular examples include NB-IoT and LoRaWAN.

IoT 123
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CDP Data Visualization: Self-Service Data Visualization For The Full Data Lifecycle

Cloudera

With the massive explosion of data across the enterprise — both structured and unstructured from existing sources and new innovations such as streaming and IoT — businesses have needed to find creative ways of managing their increasingly complex data lifecycle to speed time to insight.

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Migrate from Amazon Kinesis Data Analytics for SQL Applications to Amazon Kinesis Data Analytics Studio

AWS Big Data

Amazon Kinesis Data Analytics makes it easy to transform and analyze streaming data in real time. In this post, we discuss why AWS recommends moving from Kinesis Data Analytics for SQL Applications to Amazon Kinesis Data Analytics for Apache Flink to take advantage of Apache Flink’s advanced streaming capabilities.

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The 6 Layers of an IoT Solution

CDW Research Hub

Your first thought about the Internet of Things (IoT) might be of a “smart” device or sensor. However, building an IoT solution requires thought into six distinct layers, each with its own considerations and security implications. So, what are the six layers of IoT? Layer 1: IoT devices. Layer 2: Edge computing.

IoT 89
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The DataOps Vendor Landscape, 2021

DataKitchen

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Locke DataData science services.

Testing 300
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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. Suddenly advanced analytics wasn’t just for the analysts.