AWS Big Data

FEBRUARY 1, 2024

The following are some of the key business use cases that highlight this need: Trade reporting – Since the global financial crisis of 2007–2008, regulators have increased their demands and scrutiny on regulatory reporting. FactSet has several datasets available in the AWS Data Exchange marketplace, which we used for reference data.

Data Warehouse 121

Data Warehouse Dashboards Risk Management Risk 121

AWS Big Data

JUNE 29, 2023

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.

Data Analytics 73

Data Analytics Analytics IoT Data Lake 73

AWS Big Data

APRIL 20, 2023

Customers use Amazon Redshift to run their business-critical analytics on petabytes of structured and semi-structured data. Apache Spark is a popular framework that you can use to build applications for use cases such as ETL (extract, transform, and load), interactive analytics, and machine learning (ML). groupBy("qtr").sum("qtysold").select(

Data Lake 76

Data Lake Data Warehouse Sales Data-driven 76

AWS Big Data

FEBRUARY 1, 2024

The Common Crawl corpus contains petabytes of data, regularly collected since 2008, and contains raw webpage data, metadata extracts, and text extracts. In addition to determining which dataset should be used, cleansing and processing the data to the fine-tuning’s specific need is required. It is continuously updated.

Modeling 95

Modeling Metadata Data Processing Unstructured Data 95

bridgei2i

AUGUST 11, 2020

You know that, when we went through the last business downturn, 2008 in 2009, funny thing happened in 2010 turnover went up dramatically in sales and because companies started hiring again. We’ll be back with more discussions and points of view from the world of data analytics and AI.

Sales 98

Sales Enterprise B2B Digital Transformation 98

DataKitchen

MAY 10, 2021

That’s a fair point, and it places emphasis on what is most important – what best practices should data teams employ to apply observability to data analytics. We see data observability as a component of DataOps. In our definition of data observability, we put the focus on the important goal of eliminating data errors.

Testing 214

Testing Manufacturing Data Quality Statistics 214

Domino Data Lab

JANUARY 6, 2019

Lately I’ve been developing curriculum for a client for their new “Intro to Data Science” sequence of courses. I’ve been teaching data science since 2008 privately for employers – exec staff, investors, IT teams, and the data teams I’ve led – and since 2013, for industry professionals in general. That’s no problem.

Data Science 56

Data Science Machine Learning Reporting Visualization 56