AWS Big Data

APRIL 11, 2023

In this post, we discuss how to streamline inventory management forecasting systems with AWS managed analytics, AI/ML, and database services. With Amazon Athena , retailers can analyze this data to identify trends, patterns, and anomalies, and use Amazon ElastiCache for customer-facing applications with reduced latency.

Forecasting 78

Forecasting Management IoT Data-driven 78

DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. Overall, DataOps is an essential component of modern data-driven organizations. Query> DataOps. Query> Write an essay on DataOps.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

AWS Big Data

FEBRUARY 6, 2023

Use case overview Migrating Hadoop workloads to Amazon EMR accelerates big data analytics modernization, increases productivity, and reduces operational cost. Refactoring coupled compute and storage to a decoupling architecture is a modern data solution. Jiseong Kim is a Senior Data Architect at AWS ProServe.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

Data Lake 89

Data Lake Analytics Snapshot Optimization 89

CIO Business Intelligence

JUNE 29, 2022

Insights hidden in your data are essential for optimizing business operations, finetuning your customer experience, and developing new products — or new lines of business, like predictive maintenance. And as businesses contend with increasingly large amounts of data, the cloud is fast becoming the logical place where analytics work gets done.

Data Lake 115

Data Lake Analytics Data Warehouse Machine Learning 115

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 95

Data Warehouse Data Lake Analytics Data Science 95

AWS Big Data

APRIL 30, 2024

Amazon Q Developer can now generate complex data integration jobs with multiple sources, destinations, and data transformations. Generated jobs can use a variety of data transformations, including filter, project, union, join, and custom user-supplied SQL. In his spare time, he enjoys cycling with his road bike.

Data Integration 107

Data Integration Data Lake Data Warehouse Software 107

AWS Big Data

OCTOBER 27, 2023

Data integration is the foundation of robust data analytics. It encompasses the discovery, preparation, and composition of data from diverse sources. In the modern data landscape, accessing, integrating, and transforming data from diverse sources is a vital process for data-driven decision-making.

Analytics 100

Analytics Visualization Data Integration Cost-Benefit 100

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. You can use it for big data analytics and machine learning workloads.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

IBM Big Data Hub

MARCH 14, 2024

The solution: IBM databases on AWS To solve for these challenges, IBM’s portfolio of SaaS database solutions on Amazon Web Services (AWS), enables enterprises to scale applications, analytics and AI across the hybrid cloud landscape. It enables secure data sharing for analytics and AI across your ecosystem.

Cost-Benefit 79

Cost-Benefit Metadata Optimization Management 79

AWS Big Data

MARCH 3, 2023

Building data lakes from continuously changing transactional data of databases and keeping data lakes up to date is a complex task and can be an operational challenge. You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes.

Data Lake 85

Data Lake Dashboards Metrics Metadata 85

AWS Big Data

MARCH 3, 2023

In this post, we share how the AWS Data Lab helped Tricentis to improve their software as a service (SaaS) Tricentis Analytics platform with insights powered by Amazon Redshift. While aggregating, summarizing, and aligning to a common information model, all transformations must not affect the integrity of data from its source.

Software 52

Software Data Lake Testing Cost-Benefit 52

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. But this was only the tip of the analytics iceberg.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

AWS Big Data

AUGUST 1, 2023

Although Jira Cloud provides reporting capability, loading this data into a data lake will facilitate enrichment with other business data, as well as support the use of business intelligence (BI) tools and artificial intelligence (AI) and machine learning (ML) applications. Search for the Jira Cloud connector.

Data Lake 87

Data Lake Data Transformation Cost-Benefit Data-driven 87

AWS Big Data

NOVEMBER 7, 2023

Second, organizations still need transformations like cleansing, deduplication, and combining datasets for analysis and machine learning (ML). For these, AWS Glue provides fast, scalable data transformation. Within seconds of new data coming into Amazon Aurora MySQL, the data is replicated to Amazon Redshift.

Dashboards 75

Dashboards Data-driven Data Integration Data Lake 75

CIO Business Intelligence

AUGUST 3, 2023

When global technology company Lenovo started utilizing data analytics, they helped identify a new market niche for its gaming laptops, and powered remote diagnostics so their customers got the most from their servers and other devices.

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

Ontotext

FEBRUARY 12, 2024

Transferring ownership of data/datasets to domain-specific units that possess a deeper understanding of rules around the data empowers teams, improves data quality and trust, and greatly accelerates the building of data models and analytics. However, data mesh is not about introducing new technologies.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 93

Data Lake Data Warehouse Data-driven B2B 93

IBM Big Data Hub

JUNE 15, 2023

The proliferation of data silos also inhibits the unification and enrichment of data which is essential to unlocking the new insights. Moreover, increased regulatory requirements make it harder for enterprises to democratize data access and scale the adoption of analytics and artificial intelligence (AI).

Data Warehouse 91

Data Warehouse Data Lake Optimization Data-driven 91

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. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52