Peter James Thomas

AUGUST 2, 2019

Data Architecture – Definition (2). Data Catalogue. Data Community. Data Domain (contributor: Taru Väre ). Data Enrichment. Data Federation. Data Function. Data Model. Data Operating Model. Thanks to all of these for their help. Application Programming Interface (API).

Analytics 69

Analytics Data Analytics Data Architecture Statistics 69

AWS Big Data

SEPTEMBER 7, 2023

We will partition and format the server access logs with Amazon Web Services (AWS) Glue , a serverless data integration service, to generate a catalog for access logs and create dashboards for insights. These logs can track activity, such as data access patterns, lifecycle and management activity, and security events.

Metadata 99

Metadata Dashboards Metrics Visualization 99

Smarten

MAY 30, 2023

You will achieve seamless integration of Augmented Analytics and Business Intelligence Objects with easy to use, scalable integration APIs. Integrate objects (Dashboards, Crosstab, Tabular, KPIs, Graphs, Reports, models, Clickless Analytics and more).’

Slice and Dice 52

Slice and Dice Business Intelligence Cost-Benefit Dashboards 52

CIO Business Intelligence

JUNE 23, 2022

Want to manage and analyze data of all types including machine, structured, transactional, and unstructured – anywhere? Only Cloudera has the power to span multi-cloud and on-premises with a hybrid data platform. That’s where modern data architectures like data lakehouse, data fabric and data mesh come in.

IT 73

IT Data Architecture Unstructured Data Big Data 73

AWS Big Data

APRIL 26, 2023

Use Case Overview Huron’s Business Intelligence use case represents visualizations as a service, where Huron has core set of visualizations and dashboards available as products for its customers. In the next stage of the cycle, Huron’s consultants experiment with new data sources and insights that in turn fed back into the product dashboards.

Metadata 52

Metadata Dashboards Visualization Consulting 52

AWS Big Data

JUNE 6, 2023

In this post, we highlight the seamless integration of Amazon Athena and Amazon QuickSight , which enables the visualization of operational metrics for AWS Glue Data Quality rule evaluation in an efficient and effective manner. The following architecture diagram shows an overview of the complete pipeline. Choose Visualize.

Data Quality 71

Data Quality Metrics Visualization Dashboards 71

CIO Business Intelligence

SEPTEMBER 14, 2023

They’re often responsible for building algorithms for accessing raw data, too, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved.

Analytics 129

Analytics Data Science Unstructured Data Data mining 129

AWS Big Data

JANUARY 8, 2024

It aims to provide a framework to create low-latency streaming applications on the AWS Cloud using Amazon Kinesis Data Streams and AWS purpose-built data analytics services. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 112

Analytics IoT Data-driven Snapshot 112

AWS Big Data

NOVEMBER 28, 2023

We think that by automating the undifferentiated parts, we can help our customers increase the pace of their data-driven innovation by breaking down data silos and simplifying data integration. They used Amazon Aurora MySQL zero-ETL integration with Amazon Redshift to achieve this.

Data Warehouse 91

Data Warehouse Data-driven Machine Learning B2B 91

Cloudera

JANUARY 5, 2023

We foresee organizations pivoting focus beyond the algorithm to things like business-ready predictive dashboards, visualizations, and applications that simplify the use of AI systems to reach conclusions. They also address the concerns of IT teams in allowing access to organizational data. .

Cost-Benefit 52

Cost-Benefit Business Objectives Machine Learning Data Architecture 52

DataKitchen

NOVEMBER 4, 2021

Data organizations often have a mix of centralized and decentralized activity. DataOps concerns itself with the complex flow of data across teams, data centers and organizational boundaries. It expands beyond tools and data architecture and views the data organization from the perspective of its processes and workflows.

Data Processing 246

Data Processing Data Lake Cost-Benefit Testing 246

CIO Business Intelligence

JUNE 23, 2023

There are also no-code data engineering and AI/ML platforms so regular business users, as well as data engineers, scientists and DevOps staff, can rapidly develop, deploy, and derive business value.

Data Strategy 102

Data Strategy Strategy Visualization Consulting 102

AWS Big Data

NOVEMBER 13, 2023

The downstream consumers consist of business intelligence (BI) tools, with multiple data science and data analytics teams having their own WLM queues with appropriate priority values. Consequently, there was a fivefold rise in data integrations and a fivefold increase in ad hoc queries submitted to the Redshift cluster.

Data Warehouse 91

Data Warehouse Data Lake Analytics Data Science 91

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. Finally, we show you the technical information to use the tool.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

CIO Business Intelligence

AUGUST 9, 2022

Data engineers are often responsible for building algorithms for accessing raw data, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved. Data engineer vs. data architect.

Analytics 119

Analytics Data Science Statistics Unstructured Data 119

AWS Big Data

AUGUST 2, 2023

Using existing analytics tools such as Amazon Athena and Amazon QuickSight an organization can gain insight into its estimated carbon footprint. The data architecture diagram below shows an example of how you could use AWS services to calculate and visualize an organization’s estimated carbon footprint.

Data Lake 71

Data Lake Measurement Visualization Data Architecture 71

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. It’s raw, unprocessed data straight from the source.

Data Warehouse 104

Data Warehouse Testing Data Quality Reporting 104

AWS Big Data

MARCH 26, 2024

Strategize based on how your teams explore data, run analyses, wrangle data for downstream requirements, and visualize data at different levels. Plan on how you can enable your teams to use ML to move from descriptive to prescriptive analytics. The following screenshot shows an example C360 dashboard built on QuickSight.

Data Strategy 68

Data Strategy Strategy Data Warehouse Prescriptive Analytics 68

AWS Big Data

JUNE 29, 2023

Tracking such user queries as part of the centralized governance of the data warehouse helps stakeholders understand potential risks and take prompt action to mitigate them following the operational excellence pillar of the AWS Data Analytics Lens. Create a governance dashboard with the appropriate visualization type.

Data Warehouse 60

Data Warehouse Dashboards Testing Visualization 60

AWS Big Data

MARCH 3, 2023

You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes. Amazon EMR Serverless is a serverless option in Amazon EMR that makes it easy for data analysts and engineers to run open-source big data analytics frameworks without configuring, managing, and scaling clusters or servers.

Data Lake 83

Data Lake Dashboards Metrics Metadata 83

AWS Big Data

OCTOBER 18, 2023

Many customers migrate their data warehousing workloads to Amazon Redshift and benefit from the rich capabilities it offers, such as the following: Amazon Redshift seamlessly integrates with broader data, analytics, and AI or machine learning (ML) services on AWS , enabling you to choose the right tool for the right job.

Analytics 96

Analytics Data Warehouse Testing Dashboards 96

Sisense

SEPTEMBER 3, 2020

We live in a constantly-evolving world of data. That means that jobs in data big data and data analytics abound. The wide variety of data titles can be dizzying and confusing! This includes database modeling, metrics definition, dashboard design , and creating and publishing executive reports.

Statistics 97

Statistics Metrics Visualization Finance 97

AWS Big Data

JULY 14, 2023

These inputs reinforced the need of a unified data strategy across the FinOps teams. We decided to build a scalable data management product that is based on the best practices of modern data architecture. Our source system and domain teams were mapped as data producers, and they would have ownership of the datasets.

Finance 83

Finance Metadata Big Data Recreation/Entertainment 83

AWS Big Data

MAY 17, 2023

The service has grown into a multifaceted service used by tens of thousands of customers to process exabytes of data on a daily basis (1 exabyte is equivalent to 119 billion song downloads ). For example, ETL loads are often high I/O but require low CPU resources, and are very predictable because Peloton controls the process.

Data Warehouse 111

Data Warehouse Cost-Benefit Sales Data-driven 111

DataKitchen

NOVEMBER 29, 2021

Data Gets Meshier. 2022 will bring further momentum behind modular enterprise architectures like data mesh. The data mesh addresses the problems characteristic of large, complex, monolithic data architectures by dividing the system into discrete domains managed by smaller, cross-functional teams.

Testing 245

Testing Data Lake Data Architecture Manufacturing 245

BI-Survey

FEBRUARY 6, 2020

ML helps users prepare data to enhance reports and to select appropriate data visualizations in visual analysis and dashboards. Only a minority of companies say they have a modern reporting landscape and regularly base decisions on data.

Reporting 59

Reporting Optimization Enterprise Data Quality 59

Andrew White

JANUARY 9, 2022

There are many tactics to employ that might help – including data literacy; storytelling; use of our value pyramid/business value model; use of our decision intelligence model. To drive a successful Data Analytics strategy do you think it is a multidisciplinary activity and if so, what additional roles would you expect to see involved.

Analytics 64

Analytics Measurement Modeling Data-driven 64

AWS Big Data

APRIL 24, 2023

Building a data lake on Amazon Simple Storage Service (Amazon S3) provides numerous benefits for an organization. However, many use cases, like performing change data capture (CDC) from an upstream relational database to an Amazon S3-based data lake, require handling data at a record level.

Data Lake 80

Data Lake Data Governance Cost-Benefit Machine Learning 80

AWS Big Data

MARCH 25, 2024

To understand the best ways to make API calls via Apache Flink, refer to Common streaming data enrichment patterns in Amazon Kinesis Data Analytics for Apache Flink. OpenSearch Service offers visualization capabilities powered by OpenSearch Dashboards and Kibana (1.5

Data Lake 89

Data Lake Unstructured Data Management Modeling 89

DataKitchen

JUNE 1, 2022

T ools/Models/Dashboards. Is my dashboard displaying the correct data? How many models and dashboards were deployed? They have a Low Change Appetite: Teams have complicated in place data architectures and tools. Did every job that was supposed to run, actually run? Quality/Tests/Trust. Root Cause.

Risk 130

Risk Management Testing Dashboards 130

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. The biggest challenge is broken data pipelines due to highly manual processes. Figure 1 shows a manually executed data analytics pipeline.

Testing 152

Testing Metadata Dashboards Statistics 152

IBM Big Data Hub

JANUARY 17, 2023

Due to the convergence of events in the data analytics and AI landscape, many organizations are at an inflection point. From there, it can be easily accessed via dashboards by data consumers or those building into a data product.

Data-driven 56

Data-driven Enterprise Data Governance Prescriptive Analytics 56

IBM Big Data Hub

AUGUST 4, 2023

When effectively implemented, a data democracy simplifies the data stack, eliminates data gatekeepers, and makes the company’s comprehensive data platform easily accessible by different teams via a user-friendly dashboard. Beyond the technical aspects, the goals are far loftier.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

AWS Big Data

DECEMBER 18, 2023

Amazon Redshift powers data-driven decisions for tens of thousands of customers every day with a fully managed, AI-powered cloud data warehouse, delivering the best price-performance for your analytics workloads.

Data Warehouse 98

Data Warehouse Machine Learning Data-driven Data Lake 98

Jet Global

MAY 1, 2023

Their dashboards were visually stunning. In turn, end users were thrilled with the bells and whistles of charts, graphs, and dashboards. As rich, data-driven user experiences are increasingly intertwined with our daily lives, end users are demanding new standards for how they interact with their business data.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52