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Use Apache Iceberg in a data lake to support incremental data processing

AWS Big Data

To set up and test this solution, we complete the following high-level steps: Set up an S3 bucket in the curated zone to store converted data in Iceberg table format. In our tests, we observed Athena scanned 50% or less data for a given query on an Iceberg table compared to original data before conversion to Iceberg format.

Data Lake 116
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7 Ways to End Dead Digital Weight on Your Website with Analytics

Smart Data Collective

Google Analytics wasn’t launched until 2005. Keep reading to learn more about using analytics to optimize your website. Analytics is Crucial for Optimizing Websites. Web optimization positively impacts your revenue, whether you profit from advertising or sales via content distribution.

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Gain insights from historical location data using Amazon Location Service and AWS analytics services

AWS Big Data

This method uses GZIP compression to optimize storage consumption and query performance. You can test this solution yourself using the AWS Samples GitHub repository. You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches.

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11 Digital Marketing “Crimes Against Humanity”

Occam's Razor

This latter category contains things that are so obviously sub-optimal that no one should be doing them any more. Sophisticated Search Engine Optimization is mandatory in our world of Bing / Yandex / Baidu / Google. " I'd postulated this rule in 2005, it is even more true in 2011. Yet there they are. The 10/90 rule.

Marketing 126
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Digital Marketing And Analytics: Two Ladders For Magnificent Success

Occam's Razor

Progress in digital marketing and analytics in either scenario becomes painful (the organization / systems / thinking is simply not in the optimal position). During this stage you should also invest a lot in Search Engine Optimization. Or Ford (it is amazing that in 2013, for such an expensive product, it looks so… 2005).

Marketing 165
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Streaming Market Data with Flink SQL Part II: Intraday Value-at-Risk

Cloudera

It helps identify risk exposures, informs pre-trade decisions, and is reported to regulators for stress testing. 1] Dionne, Georges and Duchesne, Pierre and Pacurar, Maria, Intraday Value at Risk (Ivar) Using Tick-by-Tick Data with Application to the Toronto Stock Exchange (December 13, 2005). Intraday VaR. Citations. [1]

Risk 94
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Building a Named Entity Recognition model using a BiLSTM-CRF network

Domino Data Lab

from keras import optimizers from keras.models import Model from keras.models import Input from keras_contrib.layers import CRF from keras_contrib import losses from keras_contrib import metrics. Number of sentences in the training dataset: 43163 Number of sentences in the test dataset : 4796. Evaluation and testing. verbose=2).

Modeling 111