AWS Big Data

AUGUST 7, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. For more information, see ElectricityLoadDiagrams20112014 Data Set (Dua, D. and Karra Taniskidou, E.

Forecasting 86

Forecasting Data Warehouse Machine Learning Modeling 86

AWS Big Data

APRIL 25, 2024

As the queries finish running, an UNLOAD operation is invoked from the Redshift data warehouse to the S3 bucket in Account A. VPC endpoints are created for Amazon S3 and Secrets Manager to interact with other resources. Usually, data engineers create an Airflow Directed Acyclic Graph (DAG) and commit their changes to GitHub.

Metadata 110

Metadata Data Processing Management Testing 110

AWS Big Data

APRIL 20, 2023

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). Amazon Redshift integration for Apache Spark helps developers seamlessly build and run Apache Spark applications on Amazon Redshift data.

Data Lake 80

Data Lake Data Warehouse Sales Data-driven 80

AWS Big Data

MAY 10, 2023

A write-back is the ability to update a data mart, data warehouse, or any other database backend from within BI dashboards and analyze the updated data in near-real time within the dashboard itself. AnyCompany currently uses Amazon Redshift as their enterprise data warehouse platform and QuickSight as their BI solution.

Dashboards 80

Dashboards Data Warehouse Visualization Data Processing 80

Smart Data Collective

OCTOBER 17, 2022

In fact, you may have even heard about IDC’s new Global DataSphere Forecast, 2021-2025 , which projects that global data production and replication will expand at a compound annual growth rate of 23% during the projection period, reaching 181 zettabytes in 2025. zettabytes of data in 2020, a tenfold increase from 6.5

Big Data 108

Big Data Data-driven Recreation/Entertainment Data Governance 108

AWS Big Data

APRIL 19, 2023

Many customers run big data workloads such as extract, transform, and load (ETL) on Apache Hive to create a data warehouse on Hadoop. To configure AWS CLI interaction with AWS, refer to Quick setup. Sandeep Singh is a Lead Consultant at AWS ProServe, focused on analytics, data lake architecture, and implementation.

Metadata 82

Metadata Testing Data Lake Consulting 82

Ms SQL Girl

FEBRUARY 3, 2015

Acquiring and Preparing Data for Power View and Excel. Data Modelling Patterns 101 using Power Pivot. Creating Interactive Visualisation for Actionable Analytics. Tips and Tricks on Charts and Data Models. Using Power Query, we will retrieve corporate data and produce powerful dashboards. Introduction to Power BI.

Dashboards 40

Dashboards KPI Interactive Publishing 40

Ms SQL Girl

FEBRUARY 3, 2015

Acquiring and Preparing Data for Power View and Excel. Data Modelling Patterns 101 using Power Pivot. Creating Interactive Visualisation for Actionable Analytics. Tips and Tricks on Charts and Data Models. Using Power Query, we will retrieve corporate data and produce powerful dashboards. Introduction to Power BI.

Dashboards 40

Dashboards KPI Interactive Publishing 40

Ms SQL Girl

MARCH 30, 2015

Acquiring and Preparing Data for Power View and Excel. Data Modelling Patterns 101 using Power Pivot. Creating Interactive Visualisation for Actionable Analytics. Tips and Tricks on Charts and Data Models. Using Power Query, we will retrieve corporate data and produce powerful dashboards. Introduction to Power BI.

Dashboards 40

Dashboards Visualization KPI Interactive 40

Ms SQL Girl

MARCH 30, 2015

Acquiring and Preparing Data for Power View and Excel. Data Modelling Patterns 101 using Power Pivot. Creating Interactive Visualisation for Actionable Analytics. Tips and Tricks on Charts and Data Models. Using Power Query, we will retrieve corporate data and produce powerful dashboards. Introduction to Power BI.

Dashboards 40

Dashboards Visualization KPI Interactive 40

Domino Data Lab

APRIL 3, 2019

Most of the data management moved to back-end servers, e.g., databases. So we had three tiers providing a separation of concerns: presentation, logic, data. Note that data warehouse (DW) and business intelligence (BI) practices both emerged circa 1990. We keep feeding the monster data.

Data Governance 84

Data Governance Machine Learning Metadata Data Science 84

Domino Data Lab

JULY 22, 2019

By virtue of that, if you take those log files of customers interactions, you aggregate them, then you take that aggregated data, run machine learning models on them, you can produce data products that you feed back into your web apps, and then you get this kind of effect in business. You also had the launch of smartphones.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Jet Global

SEPTEMBER 22, 2023

For application teams and users, having access to insightful and actionable data is not just a luxury; it’s a necessity. You can create a query like this: “Please analyze this dataset and let me know interesting facts you see: Rows: (All) Quarter 1, 2012 Quarter 2, 2012 Quarter 3, 2012 … Cells: 4,117,344.28

Dashboards 52

Dashboards Data-driven Visualization Interactive 52