DataKitchen

JANUARY 25, 2022

There’s no shortage of consultants who will promise to manage the end-to-end lifecycle of data from integration to transformation to visualization. . The challenge is that data engineering and analytics are incredibly complex. For example, DataOps can be used to automate data integration.

Consulting 244

Consulting Testing Data Lake Data Quality 244

AWS Big Data

DECEMBER 21, 2023

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. AWS Glue provides both visual and code-based interfaces to make data integration effortless. Choose Create job and Visual ETL. Choose Create connection.

Analytics 96

Analytics IT Data Lake Visualization 96

AWS Big Data

JANUARY 26, 2023

AWS Glue is a serverless, scalable data integration service that makes it easier to discover, prepare, move, and integrate data from multiple sources. AWS Glue provides an extensible architecture that enables users with different data processing use cases.

Data Lake 110

Data Lake Big Data Software Interactive 110

AWS Big Data

NOVEMBER 20, 2023

For any modern data-driven company, having smooth data integration pipelines is crucial. These pipelines pull data from various sources, transform it, and load it into destination systems for analytics and reporting. The following is a visual representation of an example job where the number of workers is 10.

Metrics 95

Metrics Data Lake Cost-Benefit Dashboards 95

AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. DeeQu is optimized to run data quality rules in minimal passes that makes it efficient.

Data Quality 94

Data Quality Statistics Data Lake Visualization 94

AWS Big Data

OCTOBER 19, 2023

Data lakes and data warehouses are two of the most important data storage and management technologies in a modern data architecture. Data lakes store all of an organization’s data, regardless of its format or structure.

Data Lake 112

Data Lake Data Warehouse Visualization Snapshot 112

AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. As part of the transformation, the objects need to be treated to ensure data privacy (for example, PII redaction).

Data Governance 95

Data Governance Unstructured Data Metadata Data Lake 95

BizAcuity

MAY 16, 2022

So, make sure you have a data strategy in place. Data Integration. The easiest way to tap into data is integrating all your data to get a detailed understanding of your operations and your customers. Data mining. Data mining allows refining and analyzing of the data on a near-real time basis.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

CIO Business Intelligence

AUGUST 2, 2023

The layer cake metaphor shifts the data discussion from an IT discussion to the intersection of business strategy and technology. So it’s about how we create layers from the business concept, like advancing discovery, all the way down to a technology solution, like a visualization tool. Does the data live in one or many clouds?

Manufacturing 98

Manufacturing Data Architecture Strategy Data Strategy 98

AWS Big Data

JUNE 28, 2023

QuickSight makes it incredibly simple and intuitive to get to answers with Amazon QuickSight Q , which allows users to ask business questions about their data in natural language and receive answers quickly through data visualizations. Improving the zero-ETL performance is a continuous goal for AWS.

Analytics 69

Analytics Data Warehouse Data Lake Data-driven 69

AWS Big Data

JUNE 26, 2023

Companies are faced with the daunting task of ingesting all this data, cleansing it, and using it to provide outstanding customer experience. Typically, companies ingest data from multiple sources into their data lake to derive valuable insights from the data. Jupyter notebooks are web-based interactive platforms.

Insurance 80

Insurance Visualization Data Lake Metrics 80

erwin

OCTOBER 8, 2020

The desire to modernize technology, over time, leads to acquiring many different systems with various data entry points and transformation rules for data as it moves into and across the organization. Regulatory compliance is also a major driver of data governance (e.g., GDPR, CCPA, HIPAA, SOX, PIC DSS).

Data Governance 145

Data Governance Metadata Testing Data Lake 145

David Menninger's Analyst Perspectives

JANUARY 21, 2022

Automating this process using natural language processing (NLP) and artificial intelligence and machine learning (AI/ML) enables line-of-business personnel to query the data faster, generate reports themselves without depending on IT, and make quick decisions.

Analytics 130

Analytics Machine Learning Visualization Reporting 130

Cloudera

JULY 18, 2018

For those asking big questions, in the case of healthcare, an incredible amount of insight remains hidden away in troves of clinical notes, EHR data, medical images, and omics data. To arrive at quality data, organizations are spending significant levels of effort on data integration, visualization, and deployment activities.

Machine Learning 50

Machine Learning Predictive Analytics Analytics Prescriptive Analytics 50

AWS Big Data

MARCH 20, 2023

In the first post of this series , we described how AWS Glue for Apache Spark works with Apache Hudi, Linux Foundation Delta Lake, and Apache Iceberg datasets tables using the native support of those data lake formats. Even without prior experience using Hudi, Delta Lake or Iceberg, you can easily achieve typical use cases.

Visualization 80

Visualization Data Lake Snapshot Big Data 80

Andrew White

OCTOBER 22, 2021

Lakehouse (data warehouse and data lake working together) 8. Data Literacy, training, coordination, collaboration 8. Data Management Infrastructure/Data Fabric 5. Data Integration tactics 4. Enterprise Data Manager 1. Web and Data Services Manager 1. Specific Vendor Questions 5.

IT 52

IT Data Lake Strategy Data Science 52

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Jet Global

OCTOBER 7, 2020

It uses its own data mart, which cannot be customized in any way. Power BI is an analytical tool for data visualization and discovery. When working with D365 F&SCM data, it typically requires specialized programming skills to develop reports or to make changes to existing reports.

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

AWS Big Data

FEBRUARY 13, 2024

AWS Glue has made this more straightforward with the launch of AWS Glue job observability metrics , which provide valuable insights into your data integration pipelines built on AWS Glue. With Grafana, you can create, explore, and share visually rich, data-driven dashboards. Graph lines are visualized per job.

Metrics 97

Metrics Dashboards Visualization Key Performance Indicator 97

AWS Big Data

NOVEMBER 22, 2023

Apache Hudi is an open table format that brings database and data warehouse capabilities to data lakes. Apache Hudi helps data engineers manage complex challenges, such as managing continuously evolving datasets with transactions while maintaining query performance. Under Administration , choose Data catalog settings.

Data Lake 92

Data Lake Snapshot Metadata Optimization 92

AWS Big Data

OCTOBER 27, 2023

Data integration is the foundation of robust data analytics. It encompasses the discovery, preparation, and composition of data from diverse sources. In the modern data landscape, accessing, integrating, and transforming data from diverse sources is a vital process for data-driven decision-making.

Analytics 95

Analytics Visualization Data Integration Cost-Benefit 95

AWS Big Data

NOVEMBER 30, 2023

In this post, we explore how to use the AWS Glue native connector for Teradata Vantage to streamline data integrations and unlock the full potential of your data. Businesses often rely on Amazon Simple Storage Service (Amazon S3) for storing large amounts of data from various data sources in a cost-effective and secure manner.

IT 96

IT Visualization Machine Learning Data Integration 96

AWS Big Data

MARCH 27, 2024

AWS has invested in a zero-ETL (extract, transform, and load) future so that builders can focus more on creating value from data, instead of having to spend time preparing data for analysis. This means you no longer have to create an external schema in Amazon Redshift to use the data lake tables cataloged in the Data Catalog.

Data Analytics 91

Data Analytics Analytics Data Warehouse Data Lake 91

AWS Big Data

NOVEMBER 29, 2023

Zero-ETL integration also enables you to load and analyze data from multiple operational database clusters in a new or existing Amazon Redshift instance to derive holistic insights across many applications. Learn more about the zero-ETL integrations, data lake performance enhancements, and other announcements below.

Data Warehouse 100

Data Warehouse Data Lake Analytics Machine Learning 100

AWS Big Data

APRIL 20, 2023

In a modern data architecture, unified analytics enable you to access the data you need, whether it’s stored in a data lake or a data warehouse. One of the most common use cases for data preparation on Amazon Redshift is to ingest and transform data from different data stores into an Amazon Redshift data warehouse.

Visualization 78

Visualization Data Warehouse Big Data Data Lake 78

Alation

MAY 16, 2023

Data Pipeline Use Cases Here are just a few examples of the goals you can achieve with a robust data pipeline: Data Prep for Visualization Data pipelines can facilitate easier data visualization by gathering and transforming the necessary data into a usable state.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

AWS Big Data

MAY 9, 2023

Hundreds of thousands of customers use AWS Glue , a serverless data integration service, to discover, prepare, and combine data for analytics, machine learning (ML), and application development. AWS Glue for Apache Spark jobs work with your code and configuration of the number of data processing units (DPU).

Data Lake 88

Data Lake Cost-Benefit Data Integration Data Transformation 88

AWS Big Data

NOVEMBER 29, 2023

With Amazon Bedrock , you can privately customize FMs for your specific use case using a small set of your own labeled data through a visual interface without writing any code. You also need services to store data for analysis and machine learning (ML) like Amazon Simple Storage Service (Amazon S3).

Data Warehouse 109

Data Warehouse Data Lake Data Integration Dashboards 109

Ontotext

MARCH 8, 2023

As such, most large financial organizations have moved their data to a data lake or a data warehouse to understand and manage financial risk in one place. Yet, the biggest challenge for risk analysis continues to suffer from lack of a scalable way of understanding how data is interrelated.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

AWS Big Data

FEBRUARY 1, 2023

With data volumes exhibiting a double-digit percentage growth rate year on year and the COVID pandemic disrupting global logistics in 2021, it became more critical to scale and generate near-real-time data. You can visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

AWS Big Data

NOVEMBER 20, 2023

In AWS, hundreds of thousands of customers use AWS Glue , a serverless data integration service, to discover, combine, and prepare data for analytics and machine learning. The serverless Spark UI parses a Spark event log file generated in your S3 bucket to visualize detailed information for both running and completed job runs.

Visualization 85

Visualization Optimization Data Lake Management 85

AWS Big Data

MARCH 26, 2024

Data ingestion You have to build ingestion pipelines based on factors like types of data sources (on-premises data stores, files, SaaS applications, third-party data), and flow of data (unbounded streams or batch data). Data exploration Data exploration helps unearth inconsistencies, outliers, or errors.

Data Strategy 68

Data Strategy Strategy Data Warehouse Prescriptive Analytics 68

AWS Big Data

FEBRUARY 6, 2023

For data lake customers who need to discover petabytes of data, AWS Glue crawlers are a popular way to discover and catalog data in the background. This allows users to search and find relevant data from multiple data sources. Select Visual with a source and target. Choose Create job.

Metadata 75

Metadata Data Lake Machine Learning Management 75

IBM Big Data Hub

APRIL 27, 2022

The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale. Read: The first capability of a data fabric is a semantic knowledge data catalog, but what are the other 5 core capabilities of a data fabric? 11 May 2021. .

Management 88

Management Metadata Data Architecture Data Lake 88

Alation

MAY 16, 2023

Data Pipeline Use Cases Here are just a few examples of the goals you can achieve with a robust data pipeline: Data Prep for Visualization Data pipelines can facilitate easier data visualization by gathering and transforming the necessary data into a usable state.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

Smart Data Collective

OCTOBER 17, 2022

A point of data entry in a given pipeline. Examples of an origin include storage systems like data lakes, data warehouses and data sources that include IoT devices, transaction processing applications, APIs or social media. The final point to which the data has to be eventually transferred is a destination.

Data Warehouse 128

Data Warehouse Data Lake Visualization Big Data 128

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. Azure Blob Storage serves as the data lake to store raw data.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130