AWS Big Data

AUGUST 3, 2023

Data analytics on operational data at near-real time is becoming a common need. Due to the exponential growth of data volume, it has become common practice to replace read replicas with data lakes to have better scalability and performance. Apache Hudi connector for AWS Glue For this post, we use AWS Glue 4.0,

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Data Lake Visualization Dashboards Insurance 79

Jet Global

SEPTEMBER 4, 2020

Its solution was to replicate data from the production database, using data entities, into a traditional relational database. Microsoft referred to this approach as “bring your own database” (BYOD). There is an established body of practice around creating, managing, and accessing OLAP data (known as “cubes”). Data Lakes.

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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

MARCH 7, 2024

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

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Data Lake Analytics Dashboards Metrics 111

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 74

AWS Big Data

JUNE 15, 2023

In today’s world, customers manage vast amounts of data in their Amazon Simple Storage Service (Amazon S3) data lakes, which requires convoluted data pipelines to continuously understand the changes in the data layout and make them available to consuming systems.

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Data Lake Metadata Cost-Benefit Management 86

AWS Big Data

JANUARY 26, 2023

AWS Glue provides an extensible architecture that enables users with different data processing use cases. A common use case is building data lakes on Amazon Simple Storage Service (Amazon S3) using AWS Glue extract, transform, and load (ETL) jobs. AWS Glue version Hudi Delta Lake Iceberg AWS Glue 3.0 AWS Glue 4.0

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AWS Big Data

JANUARY 24, 2024

AWS-powered data lakes, supported by the unmatched availability of Amazon Simple Storage Service (Amazon S3), can handle the scale, agility, and flexibility required to combine different data and analytics approaches. For more information, refer to Amazon S3: Allows read and write access to objects in an S3 Bucket.

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Snapshot Data Lake Metadata Optimization 98

AWS Big Data

JANUARY 12, 2024

Ingestion: Data lake batch, micro-batch, and streaming Many organizations land their source data into their data lake in various ways, including batch, micro-batch, and streaming jobs. Amazon AppFlow can be used to transfer data from different SaaS applications to a data lake.

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Data Lake Cost-Benefit Visualization Structured Data 92

AWS Big Data

AUGUST 3, 2023

Today’s modern data lakes span multiple accounts, AWS Regions, and lines of business in organizations. It’s important that their data solution gives them the ability to share and access data securely and safely across Regions. For example, we are using a data lake administrator role called LF-Admin.

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Data Lake Metadata Management Data Processing 84

AWS Big Data

JANUARY 17, 2024

With Amazon EMR 6.15, we launched AWS Lake Formation based fine-grained access controls (FGAC) on Open Table Formats (OTFs), including Apache Hudi, Apache Iceberg, and Delta lake. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

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Data Lake Snapshot Big Data Data-driven 91

Dataiku

SEPTEMBER 1, 2023

Lately, the concept of data experience has been gaining attention in discussions around the enterprise data stack. As the name suggests, it refers to how people interact with data in enterprise settings. Due to fragmented data setups in these companies, their data lakes have the following characteristics:

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Data Lake Data Analytics Analytics Interactive 69

AWS Big Data

MARCH 4, 2024

As enterprises collect increasing amounts of data from various sources, the structure and organization of that data often need to change over time to meet evolving analytical needs. Schema evolution enables adding, deleting, renaming, or modifying columns without needing to rewrite existing data.

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Snapshot Data Lake Metadata Recreation/Entertainment 110

AWS Big Data

OCTOBER 3, 2023

In our previous post Improve operational efficiencies of Apache Iceberg tables built on Amazon S3 data lakes , we discussed how you can implement solutions to improve operational efficiencies of your Amazon Simple Storage Service (Amazon S3) data lake that is using the Apache Iceberg open table format and running on the Amazon EMR big data platform.

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Optimization Snapshot Data Lake Metadata 108

CIO Business Intelligence

APRIL 25, 2024

For instance, a Data Cloud-triggered flow could update an account manager in Slack when shipments in an external data lake are marked as delayed. Sharing Customer 360 insights back without data replication. With zero-copy support, the insurance company wouldn’t have to load that weather data into their platform.

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AWS Big Data

OCTOBER 20, 2023

Today, we are pleased to announce new AWS Glue connectors for Azure Blob Storage and Azure Data Lake Storage that allow you to move data bi-directionally between Azure Blob Storage, Azure Data Lake Storage, and Amazon Simple Storage Service (Amazon S3). option("header","true").load("wasbs://yourblob@youraccountname.blob.core.windows.net/loadingtest-input/100mb")

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Data Lake Big Data Consulting Data Warehouse 82

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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AWS Big Data

MARCH 25, 2024

To learn more about RAG, refer to Question answering using Retrieval Augmented Generation with foundation models in Amazon SageMaker JumpStart. A RAG-based generative AI application can only produce generic responses based on its training data and the relevant documents in the knowledge base.

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Data Lake Unstructured Data Management Modeling 88

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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AWS Big Data

FEBRUARY 29, 2024

To provide a response that includes the enterprise context, each user prompt needs to be augmented with a combination of insights from structured data from the data warehouse and unstructured data from the enterprise data lake. For more information, refer to Encryption at rest and Protecting data using encryption.

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AWS Big Data

FEBRUARY 16, 2024

Many customers are extending their data warehouse capabilities to their data lake with Amazon Redshift. They are looking to further enhance their security posture where they can enforce access policies on their data lakes based on Amazon Simple Storage Service (Amazon S3). Choose Create endpoint.

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Data Lake Data Warehouse Testing Business Objectives 95

AWS Big Data

MARCH 21, 2024

For your application’s low-latency and real-time data access, you can use Lambda and DynamoDB. For longer-term data storage, you can use managed serverless connector service Amazon Data Firehose to send data to your data lake. To use the console, refer to Getting started using MSK Serverless clusters.

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Data Lake Management Modeling Optimization 94

Ontotext

APRIL 10, 2024

Data Lakes, Data Catalogs, and Findability Organizations approach data lakes as cheap storage. They move data to data lakes creating another copy – the mantra being – “ Lets move the data to a data lake and then we will figure out what to do with it”.

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Metadata Data Lake Data Warehouse Data Quality 52

AWS Big Data

AUGUST 16, 2023

Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback. For more details, refer to Creating Apache Iceberg tables. If this is the first time accessing the Lake Formation console, add yourself as the data lake administrator.

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Data Lake Metadata Snapshot Management 77

AWS Big Data

NOVEMBER 10, 2023

The data sourcing problem To ensure the reliability of PySpark data pipelines, it’s essential to have consistent record-level data from both dimensional and fact tables stored in the Enterprise Data Warehouse (EDW). These tables are then joined with tables from the Enterprise Data Lake (EDL) at runtime.

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Data Processing Data Lake Data Warehouse Optimization 91

AWS Big Data

FEBRUARY 7, 2023

AWS Glue is a serverless data integration service that makes it easy to discover, prepare, and combine data for analytics, machine learning (ML), and application development. Apache Hudi supports ACID transactions and CRUD operations on a data lake. You don’t alter queries separately in the data lake.

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AWS Big Data

JUNE 6, 2023

It supports both data quality at rest and data quality in AWS Glue extract, transform, and load (ETL) pipelines. Data quality at rest focuses on validating the data stored in data lakes, databases, or data warehouses. It ensures that the data meets specific quality standards before it is consumed.

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Data Quality Data Lake Visualization Data-driven 67

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

Dataiku

DECEMBER 30, 2022

In helping organizations around the globe set up and implement their data science and AI strategies, we often hear teams say that they’re waiting to figure out their data first before beginning to generate value with advanced analytics and AI — whether they’re referring to data quality, data silos, or centralization in a data lake.

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Data Lake IT Data Quality Data Science 64

AWS Big Data

JULY 20, 2023

Also, Hive metastore provides flexible integration with many other open-source big data software like Apache HBase, Apache Spark, Presto, and Apache Impala. A metastore is a critical part of a data lake, and having this information available, wherever it resides, is important.

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Data Lake Metadata Data Processing Big Data 79

AWS Big Data

MARCH 2, 2023

Many organizations are building data lakes to store and analyze large volumes of structured, semi-structured, and unstructured data. In addition, many teams are moving towards a data mesh architecture, which requires them to expose their data sets as easily consumable data products.

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Data Lake Testing Interactive Unstructured Data 74

AWS Big Data

MARCH 7, 2023

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users.

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AWS Big Data

NOVEMBER 20, 2023

Use case A typical workload for AWS Glue for Apache Spark jobs is to load data from a relational database to a data lake with SQL-based transformations. For instructions, refer to Create a CloudWatch alarm based on a static threshold. When the example job ran, the workerUtilization metrics showed the following trend.

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Metrics Data Lake Cost-Benefit Dashboards 93

DataKitchen

JUNE 12, 2023

I spent much time de-categorizing DataOps: we are not discussing ETL, Data Lake, or Data Science. Today we have had over 20,000 signatures , millions of page views, and copycat clones, and it is frequently used as a reference guide. It’s Customer Journey for data analytic systems.

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Testing Data Lake Dashboards Data Science 130

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. The company wanted the ability to continue processing operational data in the secondary Region in the rare event of primary Region failure.

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Data Lake Data Processing Metadata Snapshot 89

Smart Data Collective

AUGUST 17, 2022

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. It will enable you to quickly transform and load the data results into Amazon S3 data lakes or JDBC data stores.

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Data Lake Insurance Data-driven Data Processing 109

Smart Data Collective

FEBRUARY 23, 2022

Traditional relational databases provide certain benefits, but they are not suitable to handle big and various data. That is when data lake products started gaining popularity, and since then, more companies introduced lake solutions as part of their data infrastructure. How to improve indexing.

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Data Lake Cost-Benefit Optimization Big Data 98