AWS Big Data

MARCH 27, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. You can use this feature for the purpose of data ingestion throughout the POC.

Testing 96

Testing Data Warehouse Metrics Cost-Benefit 96

Sisense

APRIL 26, 2020

Companies and businesses focus a lot on data collection in order to make sure they can get valuable insights out of it. Understanding data structure is a key to unlocking its value. A data’s “structure” refers to a particular way of organizing and storing it in a database or warehouse so that it can be accessed and analyzed.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

AWS Big Data

MARCH 27, 2024

These services enable you to collect and analyze data in near real time and put a comprehensive data governance framework in place that uses granular access control to secure sensitive data from unauthorized users. To create an AWS HealthLake data store, refer to Getting started with AWS HealthLake.

Data Analytics 87

Data Analytics Analytics Data Warehouse Data Lake 87

AWS Big Data

MARCH 28, 2023

As organizations across the globe are modernizing their data platforms with data lakes on Amazon Simple Storage Service (Amazon S3), handling SCDs in data lakes can be challenging.

Data Lake 68

Data Lake Testing Snapshot Sales 68

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

Data Warehouse 88

Data Warehouse Data Lake Analytics Data Science 88

AWS Big Data

OCTOBER 25, 2023

Most companies produce and consume unstructured data such as documents, emails, web pages, engagement center phone calls, and social media. By some estimates, unstructured data can make up to 80–90% of all new enterprise data and is growing many times faster than structured data.

Unstructured Data 115

Unstructured Data Metadata Management Analytics 115

AWS Big Data

JULY 12, 2023

Amazon Redshift helps you break down the data silos and allows you to run unified, self-service, real-time, and predictive analytics on all data across your operational databases, data lake, data warehouse, and third-party datasets with built-in governance. This is often a laborious and error-prone process.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

AWS Big Data

AUGUST 16, 2023

Apache Iceberg is an open table format for very large analytic datasets. Iceberg manages large collections of files as tables, and it supports modern analytical data lake operations such as record-level insert, update, delete, and time travel queries. We use a sample JSON file as input to Amazon DynamoDB.

Data Lake 68

Data Lake Metadata Testing Snapshot 68

AWS Big Data

JANUARY 22, 2024

They classified the metrics and indicators in the following categories: Data usage – A clear understanding of who is consuming what data source, materialized with a mapping of consumers and producers. In this approach, teams responsible for generating data are referred to as producers.

Data-driven 82

Data-driven Advertising Metadata Data Architecture 82

AWS Big Data

MARCH 26, 2024

It is prudent to consolidate this data into a single customer view, serving as a primary reference for downstream applications, ranging from ecommerce platforms to CRM systems. This consolidated view acts as a liaison between the data platform and customer-centric applications.

Data Strategy 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

Alation

JULY 19, 2022

As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming. Obstacles, such as user roles, permissions, and approval request prevent speedy data access.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. These two functions are nearly inseparable as we move further into a world of analytics that blends sources of varying volume, variety, veracity, and velocity. One solution with immense potential is ”edge computing.”

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52