Cloudera

FEBRUARY 14, 2024

Introduction Apache Iceberg has recently grown in popularity because it adds data warehouse-like capabilities to your data lake making it easier to analyze all your data — structured and unstructured. The post Optimization Strategies for Iceberg Tables appeared first on Cloudera Blog. This could be very costly.

Strategy 56

Strategy Optimization Snapshot Metadata 56

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). Data Lakes. There has been a lot of talk over the past year or two in the D365F&SCM world about “data lakes.”

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

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.

Data Lake 117

Data Lake Analytics Dashboards Metrics 117

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.

Snapshot 105

Snapshot Data Lake Metadata Optimization 105

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.

Data Lake 91

Data Lake Metadata Cost-Benefit Management 91

AWS Big Data

NOVEMBER 10, 2023

Your applications can seamlessly read from and write to your Amazon Redshift data warehouse while maintaining optimal performance and transactional consistency. Additionally, you’ll benefit from performance improvements through pushdown optimizations, further enhancing the efficiency of your operations. options(**read_config).option("query",

Data Processing 96

Data Processing Data Lake Data Warehouse Optimization 96

AWS Big Data

JANUARY 12, 2024

Leadership and development teams can spend more time optimizing current solutions and even experimenting with new use cases, rather than maintaining the current infrastructure. With the ability to move fast on AWS, you also need to be responsible with the data you’re receiving and processing as you continue to scale.

Data Lake 98

Data Lake Cost-Benefit Visualization Structured Data 98

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.

Data Lake 97

Data Lake Snapshot Big Data Data-driven 97

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.

Data Lake 100

Data Lake Management Modeling Optimization 100

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")

Data Lake 87

Data Lake Big Data Consulting Data Warehouse 87

AWS Big Data

MAY 15, 2024

You can use this solution regularly as part of your cost-optimization efforts to safely remove unused EIPs to reduce your costs. Check out the GitHub repo to regularly run this analysis as part of your cost-optimization strategy to identify and release inactive EIPs to reduce costs.

Snapshot 86

Snapshot Optimization Data Lake Reporting 86

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.

Data Lake 101

Data Lake Data Warehouse Testing Business Objectives 101

AWS Big Data

NOVEMBER 22, 2023

Today, we’re making available a new capability of AWS Glue Data Catalog that allows generating column-level statistics for AWS Glue tables. These statistics are now integrated with the cost-based optimizers (CBO) of Amazon Athena and Amazon Redshift Spectrum , resulting in improved query performance and potential cost savings.

Statistics 105

Statistics Data Lake Optimization Data-driven 105

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.

Data Lake 94

Data Lake Unstructured Data Management Modeling 94

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.

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

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.

Data Lake 97

Data Lake Cost-Benefit Optimization Big Data 97

CIO Business Intelligence

OCTOBER 13, 2023

Data architect Armando Vázquez identifies eight common types of data architects: Enterprise data architect: These data architects oversee an organization’s overall data architecture, defining data architecture strategy and designing and implementing architectures.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

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.

Metrics 99

Metrics Data Lake Cost-Benefit Dashboards 99

AWS Big Data

MARCH 26, 2024

The new Data Analytics Lens offers implementation guidance you can use to deliver secure, high performance and reliable workloads, all with an eye toward maintaining cost-effectiveness and sustainability. For more information on AWS Well-Architected Lenses, refer to AWS Well-Architected. What’s new in the Data Analytics Lens?

Data Analytics 56

Data Analytics Analytics Big Data Data Lake 56

DataKitchen

DECEMBER 9, 2022

The goal of DataOps is to help organizations make better use of their data to drive business decisions and improve outcomes. ChatGPT> DataOps is a term that refers to the set of practices and tools that organizations use to improve the quality and speed of data analytics and machine learning.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

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. They should also provide optimal performance with low or no tuning. A data hub contains data at multiple levels of granularity and is often not integrated. Data repositories represent the hub.

Analytics 73

Analytics Data Warehouse Data Lake Metadata 73

AWS Big Data

FEBRUARY 6, 2023

Additionally, a TCO calculator generates the TCO estimation of an optimized EMR cluster for facilitating the migration. For more details on how to configure and schedule the log collector, refer to the yarn-log-collector GitHub repo. For more information on how to use the YARN log organizer, refer to the yarn-log-organizer GitHub repo.

Dashboards 78

Dashboards Optimization Data Lake Cost-Benefit 78

AWS Big Data

MAY 23, 2024

We also show how to take action based on the data quality results. Solution overview Let’s consider an example data quality pipeline where a data engineer ingests data from a raw zone and loads it into a curated zone in a data lake. For more information, refer to Dynamic rules. Choose Save.

Data Quality 86

Data Quality Metrics Data Lake Sales 86

AWS Big Data

AUGUST 31, 2023

Amazon Redshift enables you to directly access data stored in Amazon Simple Storage Service (Amazon S3) using SQL queries and join data across your data warehouse and data lake. With Amazon Redshift, you can query the data in your S3 data lake using a central AWS Glue metastore from your Redshift data warehouse.

Data Lake 97

Data Lake Data Warehouse Metadata Data Architecture 97

AWS Big Data

JUNE 6, 2023

Amazon EMR on EKS provides a deployment option for Amazon EMR that allows organizations to run open-source big data frameworks on Amazon Elastic Kubernetes Service (Amazon EKS). This performance-optimized runtime offered by Amazon EMR makes your Spark jobs run fast and cost-effectively. The EMR runtime provides up to 5.37

Optimization 72

Optimization Data Lake Cost-Benefit Management 72

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. Moreover, the framework should consume compute resources as optimally as possible per the size of the operational tables.

Data Lake 94

Data Lake Data Processing Metadata Snapshot 94

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 87

Enterprise Data Warehouse Snapshot Cost-Benefit 87

AWS Big Data

MAY 18, 2023

You can discover and connect to over 70 diverse data sources, manage your data in a centralized data catalog, and create, run, and monitor data integration pipelines to load data into your data lakes and your data warehouses. For more details, refer to Spark Release 3.3.0 runtime ( 3.5

Testing 80

Testing Data Lake Cost-Benefit Data Integration 80

Cloudera

OCTOBER 6, 2022

Gartner : “Digital transformation can refer to anything from IT modernization (for example, cloud computing), to digital optimization, to the invention of new digital business models.”. For example, we have some customers using their data platform originally established for compliance initiatives to drive new use cases.

Digital Transformation 84

Digital Transformation Cost-Benefit Data Lake Machine Learning 84

IBM Big Data Hub

MAY 9, 2023

Slate refers to a family of encoder-only (RoBERTa-based) models, which while not generative, are fast and effective for many enterprise NLP tasks. models are trained on IBM’s curated, enterprise-focused data lake, on our custom-designed cloud-native AI supercomputer, Vela. All watsonx.ai

Enterprise 131

Enterprise Technology Modeling Cost-Benefit 131

AWS Big Data

JANUARY 8, 2024

For security, Kinesis Data Streams provide server-side encryption so you can meet strict data management requirements by encrypting your data at rest and Amazon Virtual Private Cloud (VPC) interface endpoints to keep traffic between your Amazon VPC and Kinesis Data Streams private.

Analytics 116

Analytics IoT Data-driven Snapshot 116

AWS Big Data

APRIL 3, 2023

Tens of thousands of customers run business-critical workloads on Amazon Redshift , AWS’s fast, petabyte-scale cloud data warehouse delivering the best price-performance. With Amazon Redshift, you can query data across your data warehouse, operational data stores, and data lake using standard SQL.

Data Warehouse 100

Data Warehouse Testing Data Lake Data-driven 100

AWS Big Data

MARCH 27, 2024

Amazon Redshift is 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. It also helps you securely access your data in operational databases, data lakes, or third-party datasets with minimal movement or copying of data.

Testing 102

Testing Data Warehouse Metrics Cost-Benefit 102

AWS Big Data

JUNE 28, 2023

Another example of AWS’s investment in zero-ETL is providing the ability to query a variety of data sources without having to worry about data movement. Data analysts and data engineers can use familiar SQL commands to join data across several data sources for quick analysis, and store the results in Amazon S3 for subsequent use.

Analytics 71

Analytics Data Warehouse Data Lake Data-driven 71

AWS Big Data

FEBRUARY 6, 2023

When migrating Hadoop workloads to Amazon EMR , it’s often difficult to identify the optimal cluster configuration without analyzing existing workloads by hand. It enables compute such as EMR instances and storage such as Amazon Simple Storage Service (Amazon S3) data lakes to scale. For more information, see the GitHub repo.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

AWS Big Data

MAY 25, 2023

Many organizations today are using AWS Glue to build ETL pipelines that bring data from disparate sources and store the data in repositories like a data lake, database, or data warehouse for further consumption. jobs because this feature will help reduce cost and optimize your ETL jobs.

Reporting 71

Reporting Metrics Optimization Data Lake 71

AWS Big Data

JULY 28, 2023

However, Athena also allows you to query data stored in 30 different data sources—in addition to Amazon S3—including relational, non-relational, and object stores running on premises or in other cloud environments. In Athena, we refer to queries on non-Amazon S3 data sources as federated queries.

Big Data 82

Big Data Data Architecture Data Lake Interactive 82