AWS Big Data

SEPTEMBER 13, 2023

A modern data architecture is an evolutionary architecture pattern designed to integrate a data lake, data warehouse, and purpose-built stores with a unified governance model. Of those tables, some are larger (such as in terms of record volume) than others, and some are updated more frequently than others.

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Data Lake Data Processing Metadata Snapshot 104

Jet Global

NOVEMBER 5, 2020

That stands for “bring your own database,” and it refers to a model in which core ERP data are replicated to a separate standalone database used exclusively for reporting. OLAP reporting based on a data warehouse model is a well-proven solution for companies with robust reporting requirements.

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Data Lake OLAP Data Warehouse Unstructured Data 98

AWS Big Data

DECEMBER 12, 2024

One-time and complex queries are two common scenarios in enterprise data analytics. Complex queries, on the other hand, refer to large-scale data processing and in-depth analysis based on petabyte-level data warehouses in massive data scenarios. Here, data modeling uses dbt on Amazon Redshift.

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AWS Big Data

OCTOBER 14, 2024

Enterprise data is brought into data lakes and data warehouses to carry out analytical, reporting, and data science use cases using AWS analytical services like Amazon Athena , Amazon Redshift , Amazon EMR , and so on. foundation model (FM) in Amazon Bedrock as the LLM. Can it also help write SQL queries?

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Metadata Data Lake Modeling Data Warehouse 89

DataKitchen

AUGUST 19, 2021

Figure 3 shows an example processing architecture with data flowing in from internal and external sources. Each data source is updated on its own schedule, for example, daily, weekly or monthly. The data scientists and analysts have what they need to build analytics for the user. The new Recipes run, and BOOM! Conclusion.

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Data Warehouse Data Lake Manufacturing Testing 246

Jet Global

SEPTEMBER 4, 2020

Consultants and developers familiar with the AX data model could query the database using any number of different tools, including a myriad of different report writers. Data entities are more secure and arguably easier to master than the relational database model, but one downside is there are lots of them! Data Lakes.

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O'Reilly on Data

OCTOBER 19, 2021

Let’s start by considering the job of a non-ML software engineer: writing traditional software deals with well-defined, narrowly-scoped inputs, which the engineer can exhaustively and cleanly model in the code. Not only is data larger, but models—deep learning models in particular—are much larger than before. Compute.

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AWS Big Data

JUNE 10, 2024

For detailed information on managing your Apache Hive metastore using Lake Formation permissions, refer to Query your Apache Hive metastore with AWS Lake Formation permissions. In this post, we present a methodology for deploying a data mesh consisting of multiple Hive data warehouses across EMR clusters.

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AWS Big Data

NOVEMBER 7, 2024

Custom context enhances the AI model’s understanding of your specific data model, business logic, and query patterns, allowing it to generate more relevant and accurate SQL recommendations. Within this feature, user data is secure and private. Your data is not shared across accounts.

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Metadata Sales Data Warehouse Optimization 97

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.

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Data Lake Data Transformation Data-driven Cost-Benefit 92

AWS Big Data

APRIL 8, 2025

In modern data architectures, Apache Iceberg has emerged as a popular table format for data lakes, offering key features including ACID transactions and concurrent write support. For more detailed configuration, refer to Write properties in the Iceberg documentation.

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Snapshot Management Metadata Big Data 117

AWS Big Data

JULY 21, 2023

Data-driven organizations treat data as an asset and use it across different lines of business (LOBs) to drive timely insights and better business decisions. This leads to having data across many instances of data warehouses and data lakes using a modern data architecture in separate AWS accounts.

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Data Lake Data Warehouse Marketing Management 93

AWS Big Data

JANUARY 9, 2025

Iceberg offers distinct advantages through its metadata layer over Parquet, such as improved data management, performance optimization, and integration with various query engines. Unlike direct Amazon S3 access, Iceberg supports these operations on petabyte-scale data lakes without requiring complex custom code.

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Metadata Snapshot Cost-Benefit Optimization 107

erwin

AUGUST 15, 2022

For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. This blog is an introduction to some advanced NoSQL and data lake database design techniques (while avoiding common pitfalls) is noteworthy. Data Modeling.

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Data Lake Modeling Unstructured Data Data Warehouse 52

AWS Big Data

APRIL 11, 2023

By collecting data from store sensors using AWS IoT Core , ingesting it using AWS Lambda to Amazon Aurora Serverless , and transforming it using AWS Glue from a database to an Amazon Simple Storage Service (Amazon S3) data lake, retailers can gain deep insights into their inventory and customer behavior.

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Forecasting Management IoT Data-driven 84

CIO Business Intelligence

JULY 31, 2024

This year, however, Salesforce has accelerated its agenda, integrating much of its recent work with large language models (LLMs) and machine learning into a low-code tool called Einstein 1 Studio. Einstein 1 Studio is a set of low-code tools to create, customize, and embed AI models in Salesforce workflows. What is Einstein 1 Studio?

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Data Lake IT Sales Experimentation 119

AWS Big Data

OCTOBER 21, 2024

However, enterprises often encounter challenges with data silos, insufficient access controls, poor governance, and quality issues. Embracing data as a product is the key to address these challenges and foster a data-driven culture. To achieve this, they plan to use machine learning (ML) models to extract insights from data.

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Sales Data-driven Data Processing Key Performance Indicator 105

AWS Big Data

FEBRUARY 13, 2025

Amazon SageMaker Unified Studio (preview) provides a unified experience for using data, analytics, and AI capabilities. You can use familiar AWS services for model development, generative AI, data processing, and analyticsall within a single, governed environment. Refer to the appendix at the end of this post for more details.

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AWS Big Data

NOVEMBER 29, 2023

We have seen a strong customer demand to expand its scope to cloud-based data lakes because data lakes are increasingly the enterprise solution for large-scale data initiatives due to their power and capabilities. The team uses dbt-glue to build a transformed gold model optimized for business intelligence (BI).

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Data Lake Management Metrics Data Warehouse 117

Alation

FEBRUARY 20, 2020

For many enterprises, a hybrid cloud data lake is no longer a trend, but becoming reality. With a cloud deployment, enterprises can leverage a “pay as you go” model; reducing the burden of incurring capital costs. Due to these needs, hybrid cloud data lakes emerged as a logical middle ground between the two consumption models.

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Data Lake ROI Metadata Cost-Benefit 52

erwin

AUGUST 31, 2023

Q: Is data modeling cool again? In today’s fast-paced digital landscape, data reigns supreme. The data-driven enterprise relies on accurate, accessible, and actionable information to make strategic decisions and drive innovation. A: It always was and is getting cooler!!

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Alation

FEBRUARY 20, 2020

Architecturally the introduction of Hadoop, a file system designed to store massive amounts of data, radically affected the cost model of data. Organizationally the innovation of self-service analytics, pioneered by Tableau and Qlik, fundamentally transformed the user model for data analysis.

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Data Lake Metadata Structured Data Big Data 52

AWS Big Data

JUNE 20, 2023

It 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. Data labeling is required for various use cases, including forecasting, computer vision, natural language processing, and speech recognition.

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Data Lake Data Science Recreation/Entertainment Experimentation 83

CIO Business Intelligence

APRIL 25, 2024

“The challenge that a lot of our customers have is that requires you to copy that data, store it in Salesforce; you have to create a place to store it; you have to create an object or field in which to store it; and then you have to maintain that pipeline of data synchronization and make sure that data is updated,” Carlson said.

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AWS Big Data

NOVEMBER 6, 2023

You can attach an EMR Studio Workspace to an EMR cluster, and use the compute power of the EMR cluster and run data science jobs on the cluster. Data is often stored in data lakes managed by AWS Lake Formation , enabling you to apply fine-grained access control through a simple grant or revoke mechanism.

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Data Lake Sales Management Testing 106

Smart Data Collective

AUGUST 17, 2022

A hybrid cloud system is a cloud deployment model combining different cloud types, using both an on-premise hardware solution and a public cloud. You can safely use an Apache Kafka cluster for seamless data movement from the on-premise hardware solution to the data lake using various cloud services like Amazon’s S3 and others.

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Data Lake Insurance Data-driven Data Processing 130

CIO Business Intelligence

JUNE 29, 2022

Taking the broadest possible interpretation of data analytics , Azure offers more than a dozen services — and that’s before you include Power BI, with its AI-powered analysis and new datamart option , or governance-oriented approaches such as Microsoft Purview. Azure Data Factory. Azure Data Lake Analytics.

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Data Lake Analytics Data Warehouse Machine Learning 116

AWS Big Data

MAY 29, 2024

Later in this post, we also briefly touch upon using CloudTrail Lake to query the data access events. AWS CloudFormation lets you model, provision, and manage AWS and third-party resources by treating infrastructure as code. Refer to Configure SAML and SCIM with Okta and IAM Identity Center for instructions.

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Data Lake Enterprise Management Business Intelligence 94

AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

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AWS Big Data

JANUARY 31, 2023

We have collected some of the key talks and solutions on data governance, data mesh, and modern data architecture published and presented in AWS re:Invent 2022, and a few data lake solutions built by customers and AWS Partners for easy reference.

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CIO Business Intelligence

OCTOBER 13, 2023

Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes. Application data architect: The application data architect designs and implements data models for specific software applications.

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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 92

Data Lake Data Warehouse Data-driven Optimization 92

AWS Big Data

OCTOBER 10, 2023

Due to the volume, velocity, and variety of data being ingested in data lakes, it can get challenging to develop and maintain policies and procedures to ensure data governance at scale for your data lake. Data confidentiality and data quality are the two essential themes for data governance.

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CIO Business Intelligence

AUGUST 9, 2024

“In cases where privacy is essential, we try to anonymize as much as possible and then move on to training the model,” says University of Florence technologist Vincenzo Laveglia. “A If after anonymization the level of information in the data is the same, the data is still useful. A balance between privacy and utility is needed.

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AWS Big Data

MARCH 25, 2024

Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. This scale and general-purpose adaptability are what makes FMs different from traditional ML models. FMs are multimodal; they work with different data types such as text, video, audio, and images.

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Data Lake Unstructured Data Management Snapshot 105

AWS Big Data

AUGUST 5, 2024

These business units have varying landscapes, where a data lake is managed by Amazon Simple Storage Service (Amazon S3) and analytics workloads are run on Amazon Redshift , 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.

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Data Lake Finance Sales Management 96

AWS Big Data

MARCH 21, 2024

You want real-time access to this data so you can monitor performance in real time, and detect and mitigate issues quickly. You also need longer-term access to this data for machine learning (ML) models to run predictive maintenance assessments, find optimization opportunities, and forecast demand.

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Data Lake Management Modeling Optimization 111