Sisense

FEBRUARY 26, 2020

In Transform to Win , we explore the challenges facing modern companies, diving into their individual digital transformations and the people who drive them. We all know that data is becoming more and more essential for businesses, as the volume of data keeps growing. Become data-driven to succeed.

Digital Transformation 90

Digital Transformation Analytics Cost-Benefit Data-driven 90

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics? Data analytics and data science are closely related.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

AWS Big Data

JUNE 6, 2023

Furthermore, it allows for necessary actions to be taken, such as rectifying errors in the data source, refining data transformation processes, and updating data quality rules. The following sample email provides operational metrics for the AWS Glue Data Quality ruleset evaluation.

Data Quality 71

Data Quality Metrics Data-driven Visualization 71

AWS Big Data

MARCH 13, 2024

You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches. Visual layouts in some screenshots in this post may look different than those on your AWS Management Console.

Analytics 90

Analytics IoT Metadata Internet of Things 90

AWS Big Data

OCTOBER 11, 2023

The availability of machine-readable files opens up new possibilities for data analytics, allowing organizations to analyze large amounts of pricing data. Using machine learning (ML) and data visualization tools, these datasets can be transformed into actionable insights that can inform decision-making.

Visualization 92

Visualization Dashboards Data-driven Gap analysis 92

AWS Big Data

NOVEMBER 15, 2023

They can use their own toolsets or rely on provided blueprints to ingest the data from source systems. Once released, consumers use datasets from different providers for analysis, machine learning (ML) workloads, and visualization. The difference lies in when and where data transformation takes place.

Dashboards 91

Dashboards Analytics Metadata Data Warehouse 91

AWS Big Data

JULY 6, 2023

It has not been specifically designed for heavy data transformation tasks. Configure the Step Functions workflow After you create the two Lambda functions, you can design the Step Functions workflow in the visual editor by using the Lambda Invoke and Map blocks, as shown in the following diagram. Add a data source block.

Machine Learning 125

Machine Learning Visualization IoT Digital Transformation 125