Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. We would like to talk about data visualization and its role in the big data movement.

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

CIO Business Intelligence

JUNE 29, 2022

The recent announcement of the Microsoft Intelligent Data Platform makes that more obvious, though analytics is only one part of that new brand. Azure Data Factory. Azure Data Explorer. Azure Data Lake Analytics. Data warehouses are designed for questions you already know you want to ask about your data, again and again.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

AWS Big Data

AUGUST 1, 2024

Large-scale data warehouse migration to the cloud is a complex and challenging endeavor that many organizations undertake to modernize their data infrastructure, enhance data management capabilities, and unlock new business opportunities. This makes sure the new data platform can meet current and future business goals.

Data Warehouse 113

Data Warehouse KPI Optimization Cost-Benefit 113

Sisense

MARCH 14, 2021

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly. Big data challenges and solutions.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

datapine

SEPTEMBER 29, 2022

With quality data at their disposal, organizations can form data warehouses for the purposes of examining trends and establishing future-facing strategies. Industry-wide, the positive ROI on quality data is well understood. Here, it all comes down to the data transformation error rate.

Data Quality 241

Data Quality Metrics Data-driven Management 241

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

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 127

Data Integration Data Lake Data Warehouse Software 127

AWS Big Data

JANUARY 30, 2025

Diagram 1: Overall architecture of the solution, using AWS Step Functions, Amazon Redshift and Amazon S3 The following AWS services were used to shape our new ETL architecture: Amazon Redshift A fully managed, petabyte-scale data warehouse service in the cloud. The following Diagram 2 shows this workflow.

Data Warehouse 53

Data Warehouse Data Architecture Machine Learning Data Transformation 53

AWS Big Data

JUNE 19, 2024

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing ETL (extract, transform, and load), business intelligence (BI), and reporting tools. All columns should masked for them.

Data Warehouse 114

Data Warehouse Testing Sales Structured Data 114

AWS Big Data

SEPTEMBER 5, 2024

Federated queries allow querying data across Amazon RDS for MySQL and PostgreSQL data sources without the need for extract, transform, and load (ETL) pipelines. If storing operational data in a data warehouse is a requirement, synchronization of tables between operational data stores and Amazon Redshift tables is supported.

IoT 111

IoT Data Warehouse Cost-Benefit Reporting 111

AWS Big Data

NOVEMBER 9, 2023

In this post, we delve into a case study for a retail use case, exploring how the Data Build Tool (dbt) was used effectively within an AWS environment to build a high-performing, efficient, and modern data platform. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

Data Warehouse 126

Data Warehouse Testing Data Quality Reporting 126

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation.

Management 98

Management Data Warehouse Digital Transformation Dashboards 98

AWS Big Data

DECEMBER 5, 2023

For files with known structures, a Redshift stored procedure is used, which takes the file location and table name as parameters and runs a COPY command to load the raw data into corresponding Redshift tables. He has more than 13 years of experience with designing and implementing large scale Big Data and Analytics solutions.

Measurement 104

Measurement Dashboards Data Warehouse Analytics 104

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 109

Enterprise Data Warehouse Data Lake Optimization 109

AWS Big Data

SEPTEMBER 6, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. With Amazon Redshift, you can analyze all your data to derive holistic insights about your business and your customers. You can also schedule stored procedures to automate data processing on Amazon Redshift. Satesh Sonti is a Sr.

Data Warehouse 115

Data Warehouse Insurance Statistics Software 115

AWS Big Data

AUGUST 13, 2024

We will create a glue studio job, add events and venue data from the SFTP server, carry out data transformations and load transformed data to s3. Big Data and ETL Solutions Architect, MWAA and AWS Glue ETL expert. Select Visual ETL in the central pane. Kamen Sharlandjiev is a Sr.

Data Processing 112

Data Processing Visualization Data Lake Data Processing 112

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 111

Data Warehouse Analytics Data Lake Data Science 111

AWS Big Data

AUGUST 9, 2024

Dafiti’s data infrastructure relies heavily on ETL and ELT processes, with approximately 2,500 unique processes run daily. Amazon Redshift at Dafiti Amazon Redshift is a fully managed data warehouse service, and was adopted by Dafiti in 2017. We started with 115 dc2.large We removed the DC2 cluster and completed the migration.

Data Lake 111

Data Lake Analytics Data Warehouse Data-driven 111

AWS Big Data

NOVEMBER 15, 2023

The difference lies in when and where data transformation takes place. In ETL, data is transformed before it’s loaded into the data warehouse. In ELT, raw data is loaded into the data warehouse first, then it’s transformed directly within the warehouse.

Dashboards 111

Dashboards Analytics Metadata Data Warehouse 111

Sisense

MAY 11, 2021

Here at Sisense, we think about this flow in five linear layers: Raw This is our data in its raw form within a data warehouse. We follow an ELT ( E xtract, L oad, T ransform) practice, as opposed to ETL, in which we opt to transform the data in the warehouse in the stages that follow. Dig into AI.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

AWS Big Data

OCTOBER 18, 2023

Apache Hive is a distributed, fault-tolerant data warehouse system that enables analytics at a massive scale. Spark SQL is an Apache Spark module for structured data processing. About the authors Amit Maindola is a Senior Data Architect focused on big data and analytics at Amazon Web Services.

Big Data 104

Big Data Data Processing Interactive Testing 104

Alation

JANUARY 17, 2023

It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse. Extract, load, Transform (ELT) tools. Data ingestion/integration services. Data orchestration tools. Better Data Culture.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Science Data Transformation 52

AWS Big Data

AUGUST 6, 2024

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it straightforward and cost-effective to analyze your data. Example data The following code shows an example of raw order data from the stream: Record1: { "orderID":"101", "email":" john.

Data Warehouse 100

Data Warehouse Data-driven Modeling Internet of Things 100

Cloudera

NOVEMBER 29, 2021

Data transforms businesses. That’s where the data lifecycle comes into play. Managing data and its flow, from the edge to the cloud, is one of the most important tasks in the process of gaining data intelligence. . The firm also worked on creating a solid pipeline from the data warehouse to the data lake.

Data Lake 77

Data Lake Data Warehouse Data Architecture Reporting 77

AWS Big Data

OCTOBER 27, 2023

Efficiency : Data transformation tasks that previously took weeks or months can now be accomplished within minutes, optimizing efficiency. Big Data and ETL Solutions Architect and Amazon AppFlow expert. He’s on a mission to make life easier for customers who are facing complex data integration challenges.

Analytics 122

Analytics Visualization Data Integration Cost-Benefit 122

AWS Big Data

DECEMBER 21, 2023

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. This enables organizations to streamline data integration and analytics with OpenSearch Service. Select the secret you created, and on the Actions menu, choose Delete.

Analytics 111

Analytics IT Data Lake Visualization 111

CDW Research Hub

OCTOBER 25, 2019

As we review data transformation and modernization strategies with our clients, we find many are investigating Snowflake as a data warehouse solution due to its ease of use, speed, and increased flexibility over a traditional data warehouse offering.

Data Warehouse 40

Data Warehouse Testing Strategy Data-driven 40

AWS Big Data

JANUARY 17, 2024

With the Amazon EMR integration with Lake Formation, you can confidently manage and process big data, unlocking insights and facilitating informed decision-making while upholding data security and governance. He is deeply passionate about applying ML/DL and big data techniques to solve real-world problems.

Data Lake 115

Data Lake Snapshot Big Data Data-driven 115

AWS Big Data

MARCH 16, 2023

Amazon Redshift is a fully managed data warehouse service that tens of thousands of customers use to manage analytics at scale. Together with price-performance , Amazon Redshift enables you to use your data to acquire new insights for your business and customers while keeping costs low.

Data Warehouse 52

Data Warehouse Testing Snapshot Modeling 52

AWS Big Data

JULY 25, 2023

The integration of Talend Cloud and Talend Stitch with Amazon Redshift Serverless can help you achieve successful business outcomes without data warehouse infrastructure management. In this post, we demonstrate how Talend easily integrates with Redshift Serverless to help you accelerate and scale data analytics with trusted data.

Data Analytics 52

Data Analytics Analytics Data Warehouse Data Processing 52

AWS Big Data

APRIL 27, 2023

With these features, you can now build data pipelines completely in standard SQL that are serverless, more simple to build, and able to operate at scale. Typically, data transformation processes are used to perform this operation, and a final consistent view is stored in an S3 bucket or folder.

Data Lake 95

Data Lake Snapshot Optimization Data Transformation 95

IBM Big Data Hub

JANUARY 18, 2023

They defined it as : “ A data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data. ”.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

AWS Big Data

FEBRUARY 8, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift enables you to run complex SQL analytics at scale and performance on terabytes to petabytes of structured and unstructured data, and make the insights widely available through popular business intelligence (BI) and analytics tools.

Data Quality 96

Data Quality Testing Data Warehouse Unstructured Data 96

IBM Big Data Hub

OCTOBER 16, 2023

How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools. A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence.

Risk 70

Risk Modeling Management Metadata 70

AWS Big Data

MAY 25, 2023

Data transformation plays a pivotal role in providing the necessary data insights for businesses in any organization, small and large. To gain these insights, customers often perform ETL (extract, transform, and load) jobs from their source systems and output an enriched dataset.

Reporting 92

Reporting Metrics Optimization Data Lake 92

IBM Big Data Hub

JULY 17, 2023

It is supported by querying, governance, and open data formats to access and share data across the hybrid cloud. Through workload optimization across multiple query engines and storage tiers, organizations can reduce data warehouse costs by up to 50 percent.

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

AWS Big Data

MARCH 3, 2023

The Amazon S3 sink connector further streams data into Amazon S3 in real time by partitioning data into fixed-sized files. Fixed-size data files avoid further latency due to unbound file sizes. As a result, data was higher quality and was streamed in real time at a much faster rate. You can follow his Twitter @simongui.

Software 52

Software Data Lake Testing Dashboards 52