IBM Big Data Hub

APRIL 25, 2023

We also made the case that query and reporting, provided by big data engines such as Presto, need to work with the Spark infrastructure framework to support advanced analytics and complex enterprise data decision-making. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures.

Optimization 56

Optimization Strategy Data Warehouse Cost-Benefit 56

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

AWS Big Data

OCTOBER 17, 2023

With Amazon Redshift, you can use standard SQL to query data across your data warehouse, operational data stores, and data lake. Migrating a data warehouse can be complex. You have to migrate terabytes or petabytes of data from your legacy system while not disrupting your production workload.

Data Warehouse 86

Data Warehouse Data Processing Data Lake Management 86

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 95

Data Lake Data Warehouse Machine Learning Cost-Benefit 95

AWS Big Data

FEBRUARY 16, 2024

Many customers are extending their data warehouse capabilities to their data lake with Amazon Redshift. They are looking to further enhance their security posture where they can enforce access policies on their data lakes based on Amazon Simple Storage Service (Amazon S3).

Data Lake 97

Data Lake Data Warehouse Testing Business Objectives 97

AWS Big Data

NOVEMBER 10, 2023

This integration expands the possibilities for AWS analytics and machine learning (ML) solutions, making the data warehouse accessible to a broader range of applications. Your applications can seamlessly read from and write to your Amazon Redshift data warehouse while maintaining optimal performance and transactional consistency.

Data Processing 93

Data Processing Data Lake Data Warehouse Optimization 93

CIO Business Intelligence

JUNE 23, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 81

Data Lake Data Warehouse Machine Learning Cost-Benefit 81

CIO Business Intelligence

OCTOBER 13, 2023

Data architect Armando Vázquez identifies eight common types of data architects: Enterprise data architect: These data architects oversee an organization’s overall data architecture, defining data architecture strategy and designing and implementing architectures.

Data Architecture 125

Data Architecture Data Warehouse Statistics Visualization 125

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 84

Data Lake Big Data Consulting Data Warehouse 84

AWS Big Data

JANUARY 17, 2024

With Amazon EMR 6.15, we launched AWS Lake Formation based fine-grained access controls (FGAC) on Open Table Formats (OTFs), including Apache Hudi, Apache Iceberg, and Delta lake. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

Data Lake 93

Data Lake Snapshot Big Data Data-driven 93

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 113

Data Lake Analytics Dashboards Metrics 113

AWS Big Data

JANUARY 24, 2024

AWS-powered data lakes, supported by the unmatched availability of Amazon Simple Storage Service (Amazon S3), can handle the scale, agility, and flexibility required to combine different data and analytics approaches. The timestamp clause lets us travel back without altering current data.

Snapshot 100

Snapshot Data Lake Metadata Optimization 100

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 84

Enterprise Data Warehouse Snapshot Cost-Benefit 84

Jen Stirrup

MAY 5, 2020

It is more than just some giant USB stick in the sky that’s going to store all of the data. It has a lot of services that you can use, such as Big Data analytics. To get the best of technology such as Artificial Intelligence or Data Science, you really, really must have your data in the right format, and a good place.

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

AWS Big Data

NOVEMBER 20, 2023

Use case A typical workload for AWS Glue for Apache Spark jobs is to load data from a relational database to a data lake with SQL-based transformations. The end benefit for you is more effective and optimized AWS Glue for Apache Spark workloads. The metrics are available in all AWS Glue supported Regions. Check it out!

Metrics 95

Metrics Data Lake Cost-Benefit Dashboards 95

AWS Big Data

MARCH 29, 2024

Analyzing historical patterns allows you to optimize performance, identify issues proactively, and improve planning. By connecting the new observability metrics to interactive QuickSight dashboards, you can uncover daily, weekly, and monthly patterns to optimize AWS Glue job usage.

Metrics 105

Metrics Visualization Dashboards Interactive 105

IBM Big Data Hub

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

AWS Big Data

JUNE 28, 2023

Another example of AWS’s investment in zero-ETL is providing the ability to query a variety of data sources without having to worry about data movement. Data analysts and data engineers can use familiar SQL commands to join data across several data sources for quick analysis, and store the results in Amazon S3 for subsequent use.

Analytics 69

Analytics Data Warehouse Data Lake Data-driven 69

AWS Big Data

MARCH 7, 2023

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. They should also provide optimal performance with low or no tuning. A data hub contains data at multiple levels of granularity and is often not integrated. Data repositories represent the hub.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map.

Data Lake 93

Data Lake Data Warehouse Metadata Data Architecture 93

Cloudera

DECEMBER 19, 2018

Natural language analytics and streaming data analytics are emerging technologies that will impact the market. Cloud computing has passed the tipping point, with most organizations comfortable moving critical data and applications to the public cloud. Big Data Technologies and Architectures.

Data Warehouse 54

Data Warehouse Analytics Big Data Data Architecture 54

AWS Big Data

MAY 30, 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. Data store – The data store used a custom data model that had been highly optimized to meet low-latency query response requirements.

Data Warehouse 85

Data Warehouse Data Lake Cost-Benefit Structured Data 85

AWS Big Data

APRIL 3, 2023

Tens of thousands of customers run business-critical workloads on Amazon Redshift , AWS’s fast, petabyte-scale cloud data warehouse delivering the best price-performance. With Amazon Redshift, you can query data across your data warehouse, operational data stores, and data lake using standard SQL.

Data Warehouse 98

Data Warehouse Testing Data Lake Data-driven 98

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 99

Testing Data Warehouse Metrics Cost-Benefit 99

AWS Big Data

MAY 18, 2023

You can discover and connect to over 70 diverse data sources, manage your data in a centralized data catalog, and create, run, and monitor data integration pipelines to load data into your data lakes and your data warehouses. AWS Glue released version 4.0 runtime ( 3.5 Since AWS Glue 4.0,

Testing 77

Testing Data Lake Cost-Benefit Data Integration 77

AWS Big Data

MARCH 25, 2024

Both engines provide native ingestion support from Kinesis Data Streams and Amazon MSK via a separate streaming pipeline to a data lake or data warehouse for analysis. For more details, refer to Create a low-latency source-to-data lake pipeline using Amazon MSK Connect, Apache Flink, and Apache Hudi.

Data Lake 90

Data Lake Unstructured Data Management Modeling 90

BizAcuity

MAY 16, 2022

When data is stored in silos and the back-end systems are not able to process the massive amounts of data seamlessly, critical information may be lost. We get critical business insights based on how well we leverage our business data. The more effectively a company uses data, the better it performs. Data mining.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

AWS Big Data

APRIL 20, 2023

Apache Spark enables you to build applications in a variety of languages, such as Java, Scala, and Python, by accessing the data in your Amazon Redshift data warehouse. Amazon Redshift integration for Apache Spark helps developers seamlessly build and run Apache Spark applications on Amazon Redshift data.

Data Lake 77

Data Lake Data Warehouse Sales Data-driven 77

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.

Data Quality 95

Data Quality Statistics Data Lake Visualization 95

Sisense

JANUARY 13, 2020

From a practical perspective, the computerization and automation of manufacturing hugely increase the data that companies acquire. And cloud data warehouses or data lakes give companies the capability to store these vast quantities of data. How data enhances product development.

Manufacturing 52

Manufacturing Data Lake Big Data Data Warehouse 52

AWS Big Data

JUNE 6, 2023

In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake. AWS Glue gave us a cost-efficient option to migrate the data and we further optimized storage cost by pruning cold data.

Analytics 55

Analytics Data Lake Testing Optimization 55

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. He is passionate about big data and data analytics. He helps enterprise customers migrate and modernize their data lake and data warehouse using AWS services.

Metadata 80

Metadata Testing Data Lake Consulting 80

AWS Big Data

SEPTEMBER 13, 2023

A modern data architecture is an evolutionary architecture pattern designed to integrate a data lake, data warehouse, and purpose-built stores with a unified governance model. Moreover, the framework should consume compute resources as optimally as possible per the size of the operational tables.

Data Lake 91

Data Lake Data Processing Metadata Snapshot 91

AWS Big Data

APRIL 19, 2023

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. This performance innovation allows Nasdaq to have a multi-use data lake between teams.

Data Warehouse 55

Data Warehouse Data Lake Unstructured Data Optimization 55

AWS Big Data

JANUARY 8, 2024

Stream Processing – An application created with Amazon Managed Service for Apache Flink can read the records from the data stream to detect and clean any errors in the time series data and enrich the data with specific metadata to optimize operational analytics. Lambda is good for event-based and stateless processing.

Analytics 113

Analytics IoT Data-driven Snapshot 113

Sisense

APRIL 26, 2020

Read on to explore more about structured vs unstructured data, why the difference between structured and unstructured data matters, and how cloud data warehouses deal with them both. Structured vs unstructured data. However, both types of data play an important role in data analysis.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

IBM Big Data Hub

OCTOBER 16, 2023

How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools. A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence.

Risk 71

Risk Modeling Management Metadata 71