AWS Big Data

NOVEMBER 7, 2024

BladeBridge offers a comprehensive suite of tools that automate much of the complex conversion work, allowing organizations to quickly and reliably transition their data analytics capabilities to the scalable Amazon Redshift data warehouse. Amazon Redshift is a fully managed data warehouse service offered by Amazon Web Services (AWS).

Data Warehouse 105

Data Warehouse Reporting Big Data Data Lake 105

AWS Big Data

SEPTEMBER 7, 2023

The AWS Glue Data Catalog is a metastore of the location, schema, and runtime metrics of your data. AWS Glue Data Catalog stores information as metadata tables, where each table specifies a single data store. Running the crawler on a schedule updates AWS Glue Data Catalog with new partitions and metadata.

Metadata 116

Metadata Dashboards Metrics Visualization 116

Alation

AUGUST 18, 2022

The challenge today is to think more broadly about what these data things could or should be. It’s important to realize that we need visibility into lineage and relationships between all data and data-related assets, including business terms, metric definitions, policies, quality rules, access controls, algorithms, etc.

Metadata 69

Metadata Visualization Statistics Data Architecture 69

AWS Big Data

FEBRUARY 26, 2025

Amazon SageMaker Lakehouse provides an open data architecture that reduces data silos and unifies data across Amazon Simple Storage Service (Amazon S3) data lakes, Redshift data warehouses, and third-party and federated data sources. connection testing, metadata retrieval, and data preview.

Analytics 61

Analytics Data Lake Metadata Data Warehouse 61

AWS Big Data

JUNE 10, 2024

Since Apache Iceberg is well supported by AWS data services and Cloudinary was already using Spark on Amazon EMR, they could integrate writing to Data Catalog and start an additional Spark cluster to handle data maintenance and compaction. For example, for certain queries, Athena runtime was 2x–4x faster than Snowflake.

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

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 131

Data Lake Analytics Dashboards Metrics 131

Octopai

JULY 9, 2020

When conducted manually, however, which has tended to be the normal mode of operation before companies discovered automation – or machine learning data lineage solutions, data lineage can be extremely tedious and time-consuming for BI & Analytics teams. A key piece of legislation that emerged from that crisis was BCBS-239.

Insurance 98

Insurance Risk Management Machine Learning Metadata 98

Cloudera

JULY 20, 2021

Invest in maturing and improving your enterprise business metrics and metadata repositories, a multitiered data architecture, continuously improving data quality, and managing data acquisitions. Then back this up by embedding compliance and security protocols throughout the insights generation cycle.

Manufacturing 106

Manufacturing Forecasting IoT Insurance 106

Cloudera

JULY 19, 2023

It is a replicated, highly-available service that is responsible for managing the metadata for all objects stored in Ozone. As Ozone scales to exabytes of data, it is important to ensure that Ozone Manager can perform at scale. The tool reads only the metadata for objects in a cluster with around 100 million keys.

Management 70

Management Metadata Metrics Optimization 70

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. Metadata tables offer insights into the physical data storage layout of the tables and offer the convenience of querying them with Athena version 3.

Data Lake 98

Data Lake Analytics Snapshot Data Quality 98

AWS Big Data

APRIL 3, 2024

Many organizations already use AWS Glue Data Quality to define and enforce data quality rules on their data, validate data against predefined rules , track data quality metrics, and monitor data quality over time using artificial intelligence (AI). option("header", "true").option("inferSchema",

Data Quality 119

Data Quality Visualization Metadata Metrics 119

Octopai

APRIL 8, 2020

While there are many factors that led to this event, one critical dynamic was the inadequacy of the data architectures supporting banks and their risk management systems. It required banks to maintain data architecture supporting risk aggregation at all times. These tools extract, sort, and integrate thousands of metrics.

Finance 52

Finance Cost-Benefit Metadata Data Architecture 52

AWS Big Data

NOVEMBER 15, 2023

It seamlessly consolidates data from various data sources within AWS, including AWS Cost Explorer (and forecasting with Cost Explorer ), AWS Trusted Advisor , and AWS Compute Optimizer. Data providers and consumers are the two fundamental users of a CDH dataset.

Dashboards 111

Dashboards Analytics Metadata Data Warehouse 111

AWS Big Data

SEPTEMBER 13, 2023

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. The File Manager Lambda function consumes those messages, parses the metadata, and inserts the metadata to the DynamoDB table odpf_file_tracker.

Data Lake 111

Data Lake Data Processing Metadata Snapshot 111

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 130

Data Lake Metadata Statistics Optimization 130

AWS Big Data

JANUARY 22, 2024

Parameters of success Acast succeeded in bootstrapping and scaling a new team- and domain-oriented data product and its corresponding infrastructure and setup, resulting in less friction in gathering insights and happier users and consumers. In this approach, teams responsible for generating data are referred to as producers.

Data-driven 118

Data-driven Advertising Metadata Data Architecture 118

AWS Big Data

OCTOBER 9, 2024

You can plan a period of parallel runs, where the legacy and new systems run in parallel, and the data is compared daily. Use functional queries to compare high-level aggregated business metrics between the source on-premises database and the target data lake. Outside of work, Himanshu likes playing chess and tennis.

Data Quality 114

Data Quality Data Lake Data Warehouse Metrics 114

AWS Big Data

DECEMBER 21, 2023

Overview of solution As a data-driven company, smava relies on the AWS Cloud to power their analytics use cases. smava ingests data from various external and internal data sources into a landing stage on the data lake based on Amazon Simple Storage Service (Amazon S3).

Data Lake 115

Data Lake Data Warehouse Data-driven B2B 115

AWS Big Data

MARCH 26, 2024

The following figure shows some of the metrics derived from the study. Profile aggregation – When you’ve uniquely identified a customer, you can build applications in Managed Service for Apache Flink to consolidate all their metadata, from name to interaction history. Then, you transform this data into a concise format.

Data Strategy 99

Data Strategy Strategy Data Warehouse Prescriptive Analytics 99

Alation

JANUARY 25, 2022

As a reminder, here’s Gartner’s definition of data fabric: “A design concept that serves as an integrated layer (fabric) of data and connecting processes. In this blog, we will focus on the “integrated layer” part of this definition by examining each of the key layers of a comprehensive data fabric in more detail.

Metadata 52

Metadata IT Data-driven Metrics 52

Cloudera

MAY 22, 2019

The program recognizes organizations that are using Cloudera’s platform and services to unlock the power of data, with massive business and social impact. Cloudera’s data superheroes design modern data architectures that work across hybrid and multi-cloud and solve complex data management and analytic use cases spanning from the Edge to AI.

Machine Learning 56

Machine Learning Data Architecture IoT Data Warehouse 56

AWS Big Data

MARCH 25, 2024

Stream processing, however, can enable the chatbot to access real-time data and adapt to changes in availability and price, providing the best guidance to the customer and enhancing the customer experience. When the model finds an anomaly or abnormal metric value, it should immediately produce an alert and notify the operator.

Data Lake 121

Data Lake Unstructured Data Management Snapshot 121

AWS Big Data

JANUARY 8, 2024

Kinesis Data Streams has native integrations with other AWS services such as AWS Glue and Amazon EventBridge to build real-time streaming applications on AWS. Refer to Amazon Kinesis Data Streams integrations for additional details. Lambda is good for event-based and stateless processing.

Analytics 134

Analytics IoT Data-driven Snapshot 134

AWS Big Data

MARCH 3, 2023

With fast and fine-grained scaling in EMR Serverless, if a pipeline runs daily and needs to process 1 GB of data one day and 100 GB of data another day, EMR Serverless automatically scales to handle that load. Monitoring – EMR Serverless sends metrics to Amazon CloudWatch at the application and job level every 1 minute.

Data Lake 98

Data Lake Dashboards Metrics Metadata 98

Sisense

SEPTEMBER 3, 2019

Think of it like something that houses the metrics used to power daily, weekly, or monthly business KPIs. roll-ups of many rows of data). Modeling Your Data for Performance. Data architecture. The data landscape has changed significantly over the last two decades. Redshift is a type of OLAP database.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

Alation

APRIL 25, 2023

More specifically, it describes the process of creating, administering, and adapting a comprehensive plan for how an organization’s data will be managed. In this way, data governance has implications for a wide range of data management disciplines, including data architecture, quality, security, metadata, and more.

Data Governance 52

Data Governance Marketing Machine Learning Sales 52

Alation

APRIL 25, 2023

More specifically, it describes the process of creating, administering, and adapting a comprehensive plan for how an organization’s data will be managed. In this way, data governance has implications for a wide range of data management disciplines, including data architecture, quality, security, metadata, and more.

Data Governance 40

Data Governance Marketing Machine Learning Sales 40

Andrew White

JANUARY 9, 2022

This is the same for scope, outcomes/metrics, practices, organization/roles, and technology. Check this out: The Foundation of an Effective Data and Analytics Operating Model — Presentation Materials. Most of D&A concerns and activities are done within EA in the Info/Data architecture domain/phases.

Analytics 64

Analytics Measurement Data-driven Modeling 64

Jet Global

MAY 1, 2023

As a result, end users can better view shared metrics (backed by accurate data), which ultimately drives performance. When treating a patient, a doctor may wish to study the patient’s vital metrics in comparison to those of their peer group. Visual Analytics Users are given data from which they can uncover new insights.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

AWS Big Data

APRIL 29, 2025

While enabling organization-wide efficiency, the team also applied these principles to the data architecture, making sure that CLEA itself operates frugally. After evaluating various tools, we built a serverless data transformation pipeline using Amazon Athena and dbt. However, our initial data architecture led to challenges.

Data Transformation 54

Data Transformation Cost-Benefit Testing Data Lake 54

DataKitchen

JANUARY 23, 2023

On the other hand, DataOps Observability refers to understanding the state and behavior of data as it flows through systems. It allows organizations to see how data is being used, where it is coming from, and how it is being transformed. Data lineage is static and often lags by weeks or months. Are problems with data tests?

Testing 130

Testing Data Governance Data Quality Data-driven 130