Data Virtualization

APRIL 21, 2022

Reading Time: 3 minutes First we had data warehouses, then came data lakes, and now the new kid on the block is the data lakehouse. But what is a data lakehouse and why should we develop one? In a way, the name describes what.

Data Lake 59

Data Lake Data Warehouse Data Integration Management 59

AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map.

Data Lake 98

Data Lake Data Warehouse Metadata Data Architecture 98

AWS Big Data

APRIL 3, 2024

licensed, 100% open-source data table format that helps simplify data processing on large datasets stored in data lakes. Data engineers use Apache Iceberg because it’s fast, efficient, and reliable at any scale and keeps records of how datasets change over time.

Data Lake 98

Data Lake Snapshot Metadata Data Architecture 98

AWS Big Data

AUGUST 22, 2024

The infrastructure provides an analytics experience to hundreds of in-house analysts, data scientists, and student-facing frontend specialists. The data engineering team is on a mission to modernize its data integration platform to be agile, adaptive, and straightforward to use.

Data Warehouse 109

Data Warehouse Data Lake Data Integration Management 109

AWS Big Data

JUNE 10, 2024

Solving the small file problem and improving query performance In modern data architectures, stream processing engines such as Amazon EMR are often used to ingest continuous streams of data into data lakes using Apache Iceberg. Iceberg provides several maintenance operations to keep your tables in good shape.

Data Lake 114

Data Lake Metadata Snapshot Analytics 114

AWS Big Data

JULY 31, 2024

In the current industry landscape, data lakes have become a cornerstone of modern data architecture, serving as repositories for vast amounts of structured and unstructured data. Maintaining data consistency and integrity across distributed data lakes is crucial for decision-making and analytics.

Data Lake 106

Data Lake Marketing Data Processing Management 106

AWS Big Data

DECEMBER 20, 2024

Amazon Q data integration , introduced in January 2024, allows you to use natural language to author extract, transform, load (ETL) jobs and operations in AWS Glue specific data abstraction DynamicFrame. In this post, we discuss how Amazon Q data integration transforms ETL workflow development.

Data Integration 85

Data Integration Visualization Data Processing Data Lake 85

AWS Big Data

JUNE 10, 2024

One of the key challenges in modern big data management is facilitating efficient data sharing and access control across multiple EMR clusters. Organizations have multiple Hive data warehouses across EMR clusters, where the metadata gets generated. Test access using SageMaker Studio in the consumer account.

Data Lake 88

Data Lake Metadata Data Warehouse Data Processing 88

AWS Big Data

SEPTEMBER 4, 2024

Effective data analytics relies on seamlessly integrating data from disparate systems through identifying, gathering, cleansing, and combining relevant data into a unified format. Reverse ETL use cases are also supported, allowing you to write data back to Salesforce.

Data Integration 82

Data Integration Data Lake Data-driven Cost-Benefit 82

AWS Big Data

DECEMBER 4, 2024

With the growing emphasis on data, organizations are constantly seeking more efficient and agile ways to integrate their data, especially from a wide variety of applications. SageMaker Lakehouse gives you the flexibility to access and query your data in-place with all Apache Iceberg compatible tools and engines.

Data Integration 89

Data Integration Data Lake Statistics Data-driven 89

AWS Big Data

DECEMBER 15, 2023

Many companies identify and label PII through manual, time-consuming, and error-prone reviews of their databases, data warehouses and data lakes, thereby rendering their sensitive data unprotected and vulnerable to regulatory penalties and breach incidents. Load data from Amazon S3 to the Redshift data warehouse.

Data Lake 109

Data Lake Data Warehouse Big Data Structured Data 109

Smart Data Collective

OCTOBER 17, 2022

A point of data entry in a given pipeline. Examples of an origin include storage systems like data lakes, data warehouses and data sources that include IoT devices, transaction processing applications, APIs or social media. The final point to which the data has to be eventually transferred is a destination.

Data Warehouse 134

Data Warehouse Data Lake Visualization Big Data 134

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 104

Data Warehouse Analytics Data Lake Machine Learning 104

In(tegrate) the Clouds

JUNE 23, 2016

This week SnapLogic posted a presentation of the 10 Modern Data Integration Platform Requirements on the company’s blog. They are: Application integration is done primarily through REST & SOAP services. Large-volume data integration is available to Hadoop-based data lakes or cloud-based data warehouses.

Data Integration 49

Data Integration Data Lake Data Warehouse Data-driven 49

Data Virtualization

NOVEMBER 24, 2022

Reading Time: 4 minutes My previous post explained that, in my mind, the data lakehouse differs hardly at all from the traditional data warehouse architectural design pattern (ADP). It consists largely of the application of new cloud-based technology to the same requirements and constraints.

Data Warehouse 52

Data Warehouse Data Integration Technology Management 52

AWS Big Data

JUNE 25, 2024

This post is co-authored by Vijay Gopalakrishnan, Director of Product, Salesforce Data Cloud. In today’s data-driven business landscape, organizations collect a wealth of data across various touch points and unify it in a central data warehouse or a data lake to deliver business insights.

Data Lake 103

Data Lake Cost-Benefit Data-driven Data Warehouse 103

CIO Business Intelligence

APRIL 25, 2022

The data lakehouse is a relatively new data architecture concept, first championed by Cloudera, which offers both storage and analytics capabilities as part of the same solution, in contrast to the concepts for data lake and data warehouse which, respectively, store data in native format, and structured data, often in SQL format.

Recreation/Entertainment 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

Cloudera

MAY 28, 2024

This form of architecture can handle data in all forms—structured, semi-structured, unstructured—blending capabilities from data warehouses and data lakes into data lakehouses.

Data Architecture 88

Data Architecture Data Lake Data Warehouse Cost-Benefit 88

AWS Big Data

DECEMBER 17, 2024

Amazon Redshift , launched in 2013, has undergone significant evolution since its inception, allowing customers to expand the horizons of data warehousing and SQL analytics. Industry-leading price-performance Amazon Redshift offers up to three times better price-performance than alternative cloud data warehouses.

Data Lake 73

Data Lake Data Warehouse Data-driven Optimization 73

BizAcuity

NOVEMBER 22, 2022

This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes. Snowflake is a cloud-native platform that eliminates the need for separate data warehouses, data lakes, and data marts allowing secure data sharing across the organization.

Data Warehouse 98

Data Warehouse Cost-Benefit Data Lake Internet of Things 98

CIO Business Intelligence

JUNE 9, 2022

All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. Marketing-focused or not, DMPs excel at negotiating with a wide array of databases, data lakes, or data warehouses, ingesting their streams of data and then cleaning, sorting, and unifying the information therein.

Management 144

Management Advertising Data Lake Sales 144

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 96

Data Warehouse Analytics Data Lake Data Science 96

CIO Business Intelligence

FEBRUARY 20, 2024

Data also needs to be sorted, annotated and labelled in order to meet the requirements of generative AI. No wonder CIO’s 2023 AI Priorities study found that data integration was the number one concern for IT leaders around generative AI integration, above security and privacy and the user experience.

Cost-Benefit 115

Cost-Benefit Data Lake Data Warehouse Data Processing 115

Data Virtualization

MARCH 16, 2023

Reading Time: 6 minutes Data lake, by combining the flexibility of object storage with the scalability and agility of cloud platforms, are becoming an increasingly popular choice as an enterprise data repository. Whether you are on Amazon Web Services (AWS) and leverage AWS S3.

Data Lake 52

Data Lake Strategy Data Integration Enterprise 52

Data Virtualization

MARCH 16, 2023

Reading Time: 6 minutes Data lake, by combining the flexibility of object storage with the scalability and agility of cloud platforms, are becoming an increasingly popular choice as an enterprise data repository. Whether you are on Amazon Web Services (AWS) and leverage AWS S3.

Data Lake 52

Data Lake Strategy Data Integration Enterprise 52

Data Virtualization

OCTOBER 5, 2022

For this reason, organizations must periodically revisit their data architectures, to ensure that they are aligned with current business goals.

Data Lake 52

Data Lake Data Architecture Data Integration Management 52

AWS Big Data

MAY 3, 2023

In today’s data-driven business environment, organizations face the challenge of efficiently preparing and transforming large amounts of data for analytics and data science purposes. Businesses need to build data warehouses and data lakes based on operational data.

Data Lake 85

Data Lake Data Warehouse Data-driven Optimization 85

Cloudera

JUNE 2, 2022

What is less frequently mentioned is that during this same time we have also seen a rapid increase of cloud services where data needs to be delivered (data lakes, lakehouses, cloud warehouses, cloud streaming systems, cloud business processes, etc.).

Enterprise 104

Enterprise Data Lake Data Collection Data-driven 104

AWS Big Data

NOVEMBER 10, 2023

This integration expands the possibilities for AWS analytics and machine learning (ML) solutions, making the data warehouse accessible to a broader range of applications. These tables are then joined with tables from the Enterprise Data Lake (EDL) at runtime. options(**read_config).option("query", cast("string")).dropDuplicates())

Data Processing 97

Data Processing Data Lake Data Warehouse Optimization 97

AWS Big Data

NOVEMBER 29, 2023

You also need services to store data for analysis and machine learning (ML) like Amazon Simple Storage Service (Amazon S3). Customers have created hundreds of thousands of data lakes on Amazon S3. We also announced that Amazon Q can help you create data integration pipelines using natural language.

Data Warehouse 116

Data Warehouse Data Lake Dashboards Data Integration 116

CIO Business Intelligence

MAY 24, 2022

The survey found the mean number of data sources per organisation to be 400, and more than 20 percent of companies surveyed to be drawing from 1,000 or more data sources to feed business intelligence and analytics systems. However, more than 99 percent of respondents said they would migrate data to the cloud over the next two years.

Data-driven 98

Data-driven Data Lake Data Warehouse Machine Learning 98

CIO Business Intelligence

DECEMBER 20, 2024

Beyond breaking down silos, modern data architectures need to provide interfaces that make it easy for users to consume data using tools fit for their jobs. Data must be able to freely move to and from data warehouses, data lakes, and data marts, and interfaces must make it easy for users to consume that data.

Data Architecture 122

Data Architecture Management Consulting Internet of Things 122

AWS Big Data

DECEMBER 4, 2024

AWS Glue is a serverless, scalable data integration service that makes it simple to discover, prepare, move, and integrate data from multiple sources. a new version of AWS Glue that accelerates data integration workloads in AWS. and Delta Lake 3.2.1 and Delta Lake 3.2.1 AWS Glue 5.0 AWS Glue 5.0

Data Lake 75

Data Lake Cost-Benefit Data Integration Optimization 75

AWS Big Data

FEBRUARY 22, 2023

In this post, we show how Ruparupa implemented an incrementally updated data lake to get insights into their business using Amazon Simple Storage Service (Amazon S3), AWS Glue , Apache Hudi , and Amazon QuickSight. An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data.

Data Lake 52

Data Lake Dashboards Cost-Benefit Data Warehouse 52

AWS Big Data

MARCH 27, 2024

AWS has invested in a zero-ETL (extract, transform, and load) future so that builders can focus more on creating value from data, instead of having to spend time preparing data for analysis. You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse.

Data Analytics 97

Data Analytics Analytics Data Warehouse Data Lake 97

AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. As part of the transformation, the objects need to be treated to ensure data privacy (for example, PII redaction).

Data Governance 101

Data Governance Unstructured Data Metadata Data Lake 101

Sisense

JULY 22, 2020

The trend has been towards using cloud-based applications and tools for different functions, such as Salesforce for sales, Marketo for marketing automation, and large-scale data storage like AWS or data lakes such as Amazon S3 , Hadoop and Microsoft Azure. Sisense provides instant access to your cloud data warehouses.

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Slice and Dice Digital Transformation Data Warehouse Data Lake 98