AWS Big Data

NOVEMBER 28, 2023

To run analytics on their operational data, customers often build solutions that are a combination of a database, a data warehouse, and an extract, transform, and load (ETL) pipeline. ETL is the process data engineers use to combine data from different sources. But integrating data isn’t easy.

Data Warehouse 90

Data Warehouse Data-driven Machine Learning B2B 90

AWS Big Data

FEBRUARY 1, 2024

Financial services customers are using data from different sources that originate at different frequencies, which includes real time, batch, and archived datasets. Additionally, they need streaming architectures to handle growing trade volumes, market volatility, and regulatory demands.

Data Warehouse 121

Data Warehouse Dashboards Risk Management Risk 121

AWS Big Data

DECEMBER 13, 2023

In collaboration with AWS, BMS identified a business need to migrate and modernize their custom extract, transform, and load (ETL) platform to a native AWS solution to reduce complexities, resources, and investment to upgrade when new Spark, Python, or AWS Glue versions are released.

Metadata 86

Metadata Data Lake Visualization Data Transformation 86

AWS Big Data

SEPTEMBER 25, 2023

Each workload type has different resource needs and different service-level agreements (SLAs). The service-level performance requirements vary by the nature of the workload and user personas accessing the datasets. We also see more and more data science and machine learning (ML) workloads.

Management 93

Management Data Warehouse Metrics Dashboards 93

AWS Big Data

MARCH 4, 2024

This post demonstrates how you can harness Iceberg, Amazon Simple Storage Service (Amazon S3), AWS Glue , AWS Lake Formation , and AWS Identity and Access Management (IAM) to implement a transactional data lake supporting seamless evolution. Similarly, partition evolution allows seamless adding, dropping, or splitting partitions. Choose Next.

Snapshot 110

Snapshot Data Lake Metadata Recreation/Entertainment 110

AWS Big Data

APRIL 25, 2024

Partitioning isn’t suitable for such high cardinality columns because you end up with small files, slow partition filtering, and high Amazon Simple Storage Service (Amazon S3) API cost (one S3 prefix is created per value of partition column). It especially works well when columns with low cardinality are chosen as the key.

Optimization 65

Optimization Data Lake Cost-Benefit Reporting 65

DataKitchen

JUNE 12, 2023

I spent much time de-categorizing DataOps: we are not discussing ETL, Data Lake, or Data Science. There is a crazy complexity in the path each person takes via a website, customer service team, and various other brand channels. How could they improve service? So how could they give a consistent message?

Testing 130

Testing Data Lake Dashboards Data Science 130

AWS Big Data

NOVEMBER 15, 2023

Attendees will discover services, strategies, and solutions for tackling any data challenge. Plan your re:Invent agenda From data ingestion and storage to analysis and visualization, AWS provides a comprehensive, integrated, and governed set of data services. He focuses on data and AI services for technical decision makers.

Broadcasting 111

Broadcasting Recreation/Entertainment Data Governance Strategy 111

AWS Big Data

NOVEMBER 9, 2023

It does this by helping teams handle the T in ETL (extract, transform, and load) processes. This popular open-source tool for data warehouse transformations won out over other ETL tools for several reasons. This popular open-source tool for data warehouse transformations won out over other ETL tools for several reasons.

Data Warehouse 103

Data Warehouse Testing Data Quality Reporting 103

DataKitchen

FEBRUARY 22, 2024

From interns to the cloud service provider, nobody is safe. By the end, you can pin an ETL failure on the office plant with convincing evidence. Let’s embark on this ironic journey through the curriculum of advanced finger-pointing, where blame is not just for breakfast anymore. It’s a full-course meal. Could never be!”

Analytics 190

Analytics Data Governance Strategy Testing 190

AWS Big Data

AUGUST 11, 2023

Services like Amazon EMR focus on offering you flexibility to support data processing workloads at scale using frameworks you’re accustomed to. Serverless services like AWS Glue minimize the need to think about servers and focus on offering additional productivity and DataOps tooling for accelerating data pipeline development.

Data Processing 95

Data Processing Cost-Benefit Optimization Interactive 95

AWS Big Data

DECEMBER 20, 2023

AWS Glue is a serverless data integration service that makes it easier to discover, prepare, and combine data for analytics, machine learning (ML), and application development. You can use AWS Glue to create, run, and monitor data integration and ETL (extract, transform, and load) pipelines and catalog your assets across multiple data stores.

Cost-Benefit 96

Cost-Benefit Optimization Big Data Data Integration 96

AWS Big Data

SEPTEMBER 13, 2023

To address these issues effectively, we propose using Amazon Managed Streaming for Apache Kafka (Amazon MSK), a fully managed Apache Kafka service that offers a seamless way to ingest and process streaming data. Set up an AWS Glue streaming ETL job to process the incoming data. For this post, we use the kafka-console-producer.sh

Management 89

Management Data Processing Interactive Metadata 89

AWS Big Data

JUNE 28, 2023

That’s why AWS is investing in a zero-ETL future so that builders can focus more on creating value from data, instead of preparing data for analysis. Challenges with ETL What is ETL? ETL can be challenging, time-consuming, and costly. Firstly, it invariably requires data engineers to create custom code.

Analytics 68

Analytics Data Warehouse Data Lake Data-driven 68

AWS Big Data

AUGUST 9, 2023

Similarly, in a serverless paradigm, application logs in Amazon CloudWatch are sourced from a variety of participating services, and traversing the lineage across logs can also present challenges. The combination of a data lake in a serverless paradigm brings significant cost and performance benefits.

Data Lake 86

Data Lake Metrics Testing Cost-Benefit 86

AWS Big Data

MARCH 27, 2024

Proof of concept overview A proof of concept (POC) is a process that uses representative data to validate whether a technology or service fulfills a customer’s technical and business requirements. For a POC on Amazon Redshift, we recommend a three-phase process of discovery, implementation, and evaluation.

Testing 98

Testing Data Warehouse Metrics Cost-Benefit 98

Cloudera

JUNE 26, 2023

Using CDSW primarily for scheduling and automating any type of workflow is a misuse of the service. Spark is primarily used to create ETL workloads by data engineers and data scientists. Use Nifi for ETL of streaming data, when real-time data processing is needed, or when data must flow from various sources rapidly and reliably.

Testing 76

Testing Data Processing Visualization Data Science 76

AWS Big Data

APRIL 3, 2023

You can also integrate AWS services like Amazon EMR , Amazon Athena , Amazon SageMaker , AWS Glue , AWS Lake Formation , and Amazon Kinesis to take advantage of all of the analytic capabilities in the AWS Cloud. With Amazon Redshift, you can query data across your data warehouse, operational data stores, and data lake using standard SQL.

Data Warehouse 96

Data Warehouse Testing Data Lake Data-driven 96

AWS Big Data

MARCH 6, 2024

Part 1 of this two-part series described how to build a pseudonymization service that converts plain text data attributes into a pseudonym or vice versa. A centralized pseudonymization service provides a unique and universally recognized architecture for generating pseudonyms.

Metrics 92

Metrics Statistics Testing Data Lake 92

AWS Big Data

JANUARY 12, 2024

Many organizations, small and large, are working to migrate and modernize their analytics workloads on Amazon Web Services (AWS). We use AWS Glue to detect, mask, and redact PII data before loading it into Amazon OpenSearch Service. Solution overview The following diagram illustrates the high-level solution architecture.

Data Lake 92

Data Lake Cost-Benefit Visualization Structured Data 92

AWS Big Data

JUNE 2, 2023

Customers are looking for tools that make it easier to migrate from other data warehouses, such as Google BigQuery, to Amazon Redshift to take advantage of the service price-performance, ease of use, security, and reliability. Amazon Redshift is a widely used, fully managed, petabyte-scale cloud data warehouse.

Metadata 108

Metadata Data Warehouse Big Data Testing 108

DataKitchen

JANUARY 19, 2022

The Matillion data integration and transformation platform enables enterprises to perform advanced analytics and business intelligence using cross-cloud platform-as-a-service offerings such as Snowflake. Adding DataOps to ETL processes is the secret to eliminating errors and dramatically improving analytic cycle times.

Testing 130

Testing Data Integration Data Warehouse Enterprise 130

datapine

JANUARY 24, 2021

In our cutthroat digital age, the importance of setting the right data analysis questions can define the overall success of a business. That being said, it seems like we’re in the midst of a data analysis crisis. Your Chance: Want to perform advanced data analysis with a few clicks? Data Is Only As Good As The Questions You Ask.

IT 317

IT Statistics KPI Data-driven 317

DataKitchen

JANUARY 25, 2022

Large enterprises integrate hundreds or thousands of asynchronous data sources into a web of pipelines that flow into visualizations and purpose-built databases that support self-service analysis. Perhaps it is no surprise that the average tenure of a CDO or CAO is only about 2.5 Here is where the loss of control begins.

Consulting 244

Consulting Testing Data Lake Data Quality 244

AWS Big Data

JULY 19, 2023

Today, we are pleased to announce a new AWS Glue connector for Google Cloud Storage that allows you to move data bi-directionally between Google Cloud Storage and Amazon Simple Storage Service (Amazon S3). With this connector, you can bring the data from Google Cloud Storage to Amazon S3.

Big Data 81

Big Data Software Consulting Unstructured Data 81

AWS Big Data

JULY 31, 2023

In the early stages of their cloud journey, customers may need guidance on modernizing their ETL workload with minimal effort and time. Customers often use many SQL scripts to select and transform the data in relational databases hosted either in an on-premises environment or on AWS and use custom workflows to manage their ETL.

Sales 52

Sales Data Warehouse Visualization Testing 52

AWS Big Data

APRIL 17, 2024

Analytics as a service (AaaS) is a business model that uses the cloud to deliver analytic capabilities on a subscription basis. Amazon Redshift is a cloud data warehouse service that offers real-time insights and predictive analytics capabilities for analyzing data from terabytes to petabytes.

Data Warehouse 91

Data Warehouse Analytics Cost-Benefit Modeling 91

AWS Big Data

MARCH 19, 2024

As businesses expand, the demand for IP addresses within the corporate network often exceeds the supply. An organization’s network is often designed with some anticipation of future requirements, but as enterprises evolve, their information technology (IT) needs surpass the previously designed network.

Optimization 86

Optimization Data-driven Management Testing 86

AWS Big Data

MARCH 7, 2024

For example, application logs and traces from web applications can be collected directly in a data lake, and a portion of that data can be moved out to a log analytics store like Amazon OpenSearch Service for daily analysis. Organizations often need to manage a high volume of data that is growing at an extraordinary rate. Example Corp.

Data Lake 111

Data Lake Analytics Dashboards Metrics 111

erwin

OCTOBER 8, 2020

These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (APIs), file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data. Automated Cloud Migration.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

AWS Big Data

JUNE 27, 2023

Integrating with AWS With the AWS technology stack, we were able to create a custom-fit solution using a regionally diverse, service-oriented model to improve our time to deliver interactive reporting to our customers while also trimming costs. With AWS, we aren’t forced to pay for a bundle with services that we don’t use.

Metrics 97

Metrics Dashboards Interactive Visualization 97

Smart Data Collective

SEPTEMBER 19, 2022

We have witnessed huge advancements in the financial industry’s service provision, thanks to big data. Big data in fintech plays a vital role, providing crucial content that impacts service delivery. Through big data insights, financial institutions can offer personalized services as well as predict consumer behavior.

Big Data 128

Big Data ROI Measurement Risk 128

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 in ETL pipelines, on the other hand, ensures the quality of data as it moves through the ETL process. Data is the lifeblood of modern businesses. However, not all data is created equal.

Data Quality 67

Data Quality Data Lake Visualization Data-driven 67

AWS Big Data

APRIL 19, 2023

Many customers run big data workloads such as extract, transform, and load (ETL) on Apache Hive to create a data warehouse on Hadoop. With this solution, we support basic orchestration and scheduling with the help of AWS services like Amazon DynamoDB and Amazon Simple Storage Service (Amazon S3).

Metadata 78

Metadata Testing Data Lake Consulting 78

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 82

Data Lake Big Data Consulting Data Warehouse 82

AWS Big Data

JUNE 23, 2023

Imperva’s data lake is based on Amazon Simple Storage Service (Amazon S3), where data is continually loaded. Imperva’s data lake is based on Amazon Simple Storage Service (Amazon S3), where data is continually loaded. Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL.

Data Lake 68

Data Lake Cost-Benefit Dashboards Data Warehouse 68

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. However, some companies use other cloud solutions, which need to be discussed as well. These infrastructures can be either in hybrid cloud or multi-cloud.

Data Lake 108

Data Lake Insurance Data-driven Data Processing 108