AWS Big Data

JUNE 8, 2023

Configure OpenSearch Service alerts to send notifications to PagerDuty We can monitor OpenSearch cluster health in two different ways: Using the OpenSearch Dashboard alerting plugin by setting up a per cluster metrics monitor. This provides a query to retrieve metrics related to the cluster health. Choose Preview query.

Data Lake 76

Data Lake Dashboards Metrics Testing 76

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 90

Data Lake Unstructured Data Management Modeling 90

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. About the Authors Krishna Rupanagunta leads a team of Data and AI Specialists at AWS.

Data Governance 95

Data Governance Unstructured Data Metadata Data Lake 95

DataKitchen

JANUARY 3, 2022

A DataOps process hub offers a way for business analytics teams to cope with fast-paced requirements without expanding staff or sacrificing quality. Analytics Hub and Spoke. The data analytics function in large enterprises is generally distributed across departments and roles. DataOps Process Hub.

Business Analytics 245

Business Analytics Analytics Testing Dashboards 245

AWS Big Data

MARCH 12, 2024

In recent years, data lakes have become a mainstream architecture, and data quality validation is a critical factor to improve the reusability and consistency of the data. In this post, we provide benchmark results of running increasingly complex data quality rulesets over a predefined test dataset.

Data Quality 88

Data Quality Measurement Testing Visualization 88

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. Complete the implementation tasks such as data ingestion and performance testing. Analyze the data and then optimize as necessary.

Testing 98

Testing Data Warehouse Metrics Cost-Benefit 98

Corinium

JUNE 6, 2019

For instance, for a variety of reasons, in the short term, CDAOS are challenged with quantifying the benefits of analytics’ investments. Some of the work is very foundational, such as building an enterprise data lake and migrating it to the cloud, which enables other more direct value-added activities such as self-service.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

IBM Big Data Hub

JUNE 8, 2022

A typical organization’s data landscape consists of a large number of data stores across workflows, business processes and business units, including but not limited to data warehouses, data marts, data lakes, ODS, cloud data stores, and CRM databases. The volume of data assets.

Data-driven 58

Data-driven Enterprise Data Governance Data Lake 58

AWS Big Data

FEBRUARY 6, 2023

Use case overview Migrating Hadoop workloads to Amazon EMR accelerates big data analytics modernization, increases productivity, and reduces operational cost. Refactoring coupled compute and storage to a decoupling architecture is a modern data solution. Jiseong Kim is a Senior Data Architect at AWS ProServe.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

Sisense

JULY 8, 2020

Product and engineering teams dig into productivity metrics or bug reports to help them better prioritize their resources. Data teams can then build tests on top of their cloud data warehouse to monitor their data sources for quality, freshness, etc. Data, analytics, and BI have radically evolved since their inception.

Data Warehouse 90

Data Warehouse Data Lake Data-driven Cost-Benefit 90

BizAcuity

MAY 16, 2022

Fast food companies like Domino’s, McDonald’s and KFC collect massive amounts of data which includes customer data and other key business metrics for their own operations. Also, it is using customer data that they experiment and roll out new products every month. Data mining.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

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 113

Data Lake Metadata Optimization Statistics 113

AWS Big Data

APRIL 11, 2023

With the proliferation of IoT devices and the abundance of data generated by them, it has become possible to collect real-time data on inventory levels, customer behavior, and other key metrics. However, analyzing large volumes of data can be a time-consuming and resource-intensive task. This is where Athena come in.

Forecasting 73

Forecasting Management IoT Data-driven 73

Cloudera

MAY 15, 2019

Barbara Eckman from Comcast is another keynote speaker, and is also presenting a breakout session about Comcast’s streaming data platform. The platform comprises ingest, transformation, and storage services in the public cloud, and on-prem RDBMS’s, EDW’s, and a large, ungoverned legacy data lake.

Enterprise 47

Enterprise Data Lake Data mining IoT 47

AWS Big Data

JANUARY 8, 2024

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 111

Analytics IoT Data-driven Snapshot 111

AWS Big Data

NOVEMBER 9, 2023

It allows users to write data transformation code, run it, and test the output, all within the framework it provides. Use case The Enterprise Data Analytics group of a large jewelry retailer embarked on their cloud journey with AWS in 2021. Third-party APIs – These provide analytics and survey data related to ecommerce websites.

Data Warehouse 104

Data Warehouse Testing Data Quality Reporting 104

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. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

Data Lake 85

Data Lake Analytics Snapshot Optimization 85

AWS Big Data

JULY 28, 2023

This query is fairly complex: it involves multiple joins and requires special knowledge of the correct way to calculate profit metrics that other end-users may not possess. For more information on using views with federated data sources, see Querying federated views. Big Data Architect on Amazon Athena. Pathik Shah is a Sr.

Big Data 77

Big Data Data Architecture Data Lake Interactive 77

IBM Big Data Hub

OCTOBER 16, 2023

Marketers use ML for lead generation, data analytics, online searches and search engine optimization (SEO). ML algorithms and data science are how recommendation engines at sites like Amazon, Netflix and StitchFix make recommendations based on a user’s taste, browsing and shopping cart history.

Machine Learning 51

Machine Learning Marketing Forecasting Modeling 51

DataKitchen

NOVEMBER 29, 2021

In 2022, data organizations will institute robust automated processes around their AI systems to make them more accountable to stakeholders. Quality test suites will enforce “equity,” like any other performance metric. Most organizations run the data factory using manual labor. Rise of the DataOps Engineer.

Testing 245

Testing Data Lake Data Architecture Manufacturing 245

AWS Big Data

FEBRUARY 22, 2023

In this post, we show how Ruparupa implemented an incrementally updated data lake to get insights into their business using Amazon Simple Storage Service (Amazon S3), AWS Glue , Apache Hudi , and Amazon QuickSight. An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data.

Data Lake 52

Data Lake Dashboards Cost-Benefit Metadata 52

datapine

AUGUST 29, 2022

The saying “knowledge is power” has never been more relevant, thanks to the widespread commercial use of big data and data analytics. The rate at which data is generated has increased exponentially in recent years. Essential Big Data And Data Analytics Insights. million searches per day and 1.2

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Alation

MARCH 21, 2023

Why is data analytics important for travel organizations? With data analytics , travel organizations can gain real-time insights about customers to make strategic decisions and improve their travel experience. How is data analytics used in the travel industry?

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

CIO Business Intelligence

MARCH 2, 2023

In general, it’s been straight forward to quantify the business impact of automation initiatives, given they typically have clear before and after business metrics. A catalyst to make this happen will be the ongoing improvements in AI-enabled data capture. million consumers.

Data Lake 141

Data Lake Forecasting B2B Optimization 141

AWS Big Data

JANUARY 24, 2023

This solution only replicates metadata in the Data Catalog, not the actual underlying data. To have a redundant data lake using Lake Formation and AWS Glue in an additional Region, we recommend replicating the Amazon S3-based storage using S3 replication , S3 sync, aws-s3-copy-sync-using-batch or S3 Batch replication process.

Data Architecture 64

Data Architecture Metadata Data Lake Snapshot 64

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. You can use it for big data analytics and machine learning workloads.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

AWS Big Data

MAY 16, 2023

Solution overview The AWS Data Lab offers accelerated, joint engineering engagements between customers and AWS technical resources to create tangible deliverables that accelerate data, analytics, artificial intelligence (AI), machine learning (ML), serverless, and container modernization initiatives.

Data Lake 69

Data Lake Cost-Benefit Optimization Testing 69

AWS Big Data

MARCH 3, 2023

Building data lakes from continuously changing transactional data of databases and keeping data lakes up to date is a complex task and can be an operational challenge. You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes.

Data Lake 80

Data Lake Dashboards Metrics Metadata 80

AWS Big Data

MARCH 26, 2024

The following figure shows some of the metrics derived from the study. The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud. Learn from this to build querying capabilities across your data lake and the data warehouse.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

DataKitchen

OCTOBER 11, 2021

The biggest challenge is broken data pipelines due to highly manual processes. Figure 1 shows a manually executed data analytics pipeline. First, a business analyst consolidates data from some public websites, an SFTP server and some downloaded email attachments, all into Excel.

Testing 152

Testing Metadata Dashboards Statistics 152

datapine

APRIL 15, 2020

These basic steps will enable you to deliver agile data analytics and BI methodology into practice, no matter the size of your company. Top 10 Tips For Agile BI & Analytics Development. Ensure the quality of production. Support collaboration and self-management.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

AWS Big Data

JULY 13, 2023

To verify the data quality of the sources through statistically-relevant metrics, AWS Glue Data Quality runs data quality tasks on relevant AWS Glue tables. Foundations for a data lake with data governance controls and data quality checks.

Optimization 88

Optimization B2B Data Quality Sales 88

AWS Big Data

JULY 12, 2023

Amazon Redshift helps you break down the data silos and allows you to run unified, self-service, real-time, and predictive analytics on all data across your operational databases, data lake, data warehouse, and third-party datasets with built-in governance.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

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. Srikant Das is an Acceleration Lab Solutions Architect at Amazon Web Services.

Data-driven 85

Data-driven Advertising Metadata Data Architecture 85

Corinium

APRIL 25, 2019

Ahead of the Chief Data Analytics Officers & Influencers, Insurance event we caught up with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity to discuss how the industry is evolving. Life insurance needs accurate data on consumer health, age and other metrics of risk.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

AWS Big Data

FEBRUARY 21, 2023

Regardless of the division or use case it is related to, dimensional data models can be used to store data obtained from tracking various processes like patient encounters, provider practice metrics, aftercare surveys, and more. It is a data modeling methodology designed for large-scale data warehouse platforms.

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

Alation

JULY 19, 2022

As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming. Obstacles, such as user roles, permissions, and approval request prevent speedy data access.

Metadata 59

Metadata Data Quality Statistics Data Science 59