AWS Big Data

JANUARY 12, 2024

Many organizations, small and large, are working to migrate and modernize their analytics workloads on Amazon Web Services (AWS). We have defined all layers and components of our design in line with the AWS Well-Architected Framework Data Analytics Lens. The data will be consumed by downstream analytical processes.

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Data Lake Cost-Benefit Visualization Structured Data 92

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 80

Data Science Data Analytics Prescriptive Analytics Analytics 80

AWS Big Data

MARCH 7, 2023

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 70

Analytics Data Warehouse Data Lake Metadata 70

AWS Big Data

JUNE 6, 2023

As most organizations, that have turned to Google Analytics (GA) as a digital analytics solution, mature they discover a more pressing need to integrate this data silo with the rest of their organization’s data to enable better analytics and resulting product development and fraud detection.

Analytics 55

Analytics Data Lake Testing Optimization 55

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")

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Data Lake Big Data Consulting Data Warehouse 82

AWS Big Data

FEBRUARY 7, 2023

In the data analytics space, organizations often deal with many tables in different databases and file formats to hold data for different business functions. Apache Hudi supports ACID transactions and CRUD operations on a data lake. It uses the native support for Apache Hudi on AWS Glue for Apache Spark.

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Data Lake Testing Big Data Management 71

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 provides support for native ingestion from Kinesis data streams or MSK topics.

Data Lake 88

Data Lake Unstructured Data Management Modeling 88

CIO Business Intelligence

APRIL 25, 2022

The data lakehouse is a relatively new data architecture concept, first championed by Cloudera, which offers both storage and analytics capabilities as part of the same solution, in contrast to the concepts for data lake and data warehouse which, respectively, store data in native format, and structured data, often in SQL format.

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Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 113

AWS Big Data

NOVEMBER 22, 2023

Data lakes are designed for storing vast amounts of raw, unstructured, or semi-structured data at a low cost, and organizations share those datasets across multiple departments and teams. The queries on these large datasets read vast amounts of data and can perform complex join operations on multiple datasets.

Statistics 99

Statistics Data Lake Optimization Data-driven 99

Cloudera

DECEMBER 11, 2020

This is what really stood out about the finalists of the Data Security and Governance category. These customers have embedded security and governance throughout their entire data and analytics lifecycle by design. Merck KGaA’s advanced analytics team had the solution. Driving innovation with secure and governed data .

Data Lake 98

Data Lake Cost-Benefit Unstructured Data Data Governance 98

Cloudera

JUNE 25, 2021

Many Cloudera customers are making the transition from being completely on-prem to cloud by either backing up their data in the cloud, or running multi-functional analytics on CDP Public cloud in AWS or Azure. The Replication Manager service facilitates both disaster recovery and data migration across different environments.

Data Lake 69

Data Lake Metadata Unstructured Data Management 69

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

Unstructured Data 104

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 104

Jet Global

OCTOBER 30, 2020

Introducing Data Lakes. Microsoft’s next option is called Azure Data Lake Services (ADLS), and it seems to be the company’s favored long-term solution to its D365 F&SCM reporting challenge. Data lake” is a generic term that refers to a fairly new development in the world of big data analytics.

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Data Lake Unstructured Data Reporting Finance 52

IBM Big Data Hub

APRIL 9, 2024

This allows the Masters to scale analytics and AI wherever their data resides, through open formats and integration with existing databases and tools. “Hole distances and pin positions vary from round to round and year to year; these factors are important as we stage the data.”

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Management IT Machine Learning Metrics 82

Sisense

APRIL 26, 2020

Structured vs unstructured data. Structured data is far easier for programs to understand, while unstructured data poses a greater challenge. However, both types of data play an important role in data analysis. Structured data. Structured data is organized in tabular format (ie.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

AWS Big Data

MARCH 28, 2023

As organizations across the globe are modernizing their data platforms with data lakes on Amazon Simple Storage Service (Amazon S3), handling SCDs in data lakes can be challenging.

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Data Lake Testing Snapshot Sales 69

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. This facilitates collaboration across isolated clusters, allowing data to be shared for innovation and analytic services.

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Testing Data Warehouse Metrics Cost-Benefit 98

IBM Big Data Hub

JULY 5, 2022

Db2’s decades of innovation and expertise running the most demanding transactional, analytical, and operational workloads have culminated today in the 2022 Gartner Peer Insights Customers’ Choice distinction for Cloud Database Management Systems. . Nedbank builds a scalable data warehouse architecture . Anywhere deployment .

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Data Lake Data Warehouse Publishing Structured Data 92

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.

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Data Warehouse Testing Data Quality Reporting 102

IBM Big Data Hub

APRIL 25, 2023

In a prior blog , we pointed out that warehouses, known for high-performance data processing for business intelligence, can quickly become expensive for new data and evolving workloads. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures. Some use case examples will help.

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Optimization Strategy Data Warehouse Cost-Benefit 57

AWS Big Data

APRIL 20, 2023

Customers use Amazon Redshift to run their business-critical analytics on petabytes of structured and semi-structured data. Apache Spark is a popular framework that you can use to build applications for use cases such as ETL (extract, transform, and load), interactive analytics, and machine learning (ML).

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Data Lake Data Warehouse Sales Data-driven 75

AWS Big Data

MARCH 27, 2024

Achieving this will also improve general public health through better and more timely interventions, identify health risks through predictive analytics, and accelerate the research and development process. This will be your online transaction processing (OLTP) data store for transactional data.

Data Analytics 89

Data Analytics Analytics Data Warehouse Data Lake 89

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed, cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. It also helps you to securely access your data in operational databases, data lakes or third-party datasets with minimal movement or copying.

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Data Warehouse Data-driven Testing Business Intelligence 81

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

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Data Warehouse Data Lake Analytics Data Science 90

AWS Big Data

JULY 19, 2023

We’ve seen that there is a demand to design applications that enable data to be portable across cloud environments and give you the ability to derive insights from one or more data sources. With this connector, you can bring the data from Google Cloud Storage to Amazon S3.

Big Data 81

Big Data Software Consulting Unstructured Data 81

Sisense

OCTOBER 6, 2020

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Sisense

APRIL 9, 2021

Instead, businesses are increasingly turning to data lakes to store massive amounts of unstructured data. Analytics from your cloud data sources are key to transforming your business, but the reality of how most companies use them lags behind expectations. The rise of data warehouses and data lakes.

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Data Lake Data Warehouse Unstructured Data Structured Data 52

Alation

FEBRUARY 20, 2020

Architecturally the introduction of Hadoop, a file system designed to store massive amounts of data, radically affected the cost model of data. Organizationally the innovation of self-service analytics, pioneered by Tableau and Qlik, fundamentally transformed the user model for data analysis. The Rise of the Data Catalog.

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Data Lake Metadata Structured Data Big Data 52

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.

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Data Lake Dashboards Cost-Benefit Metadata 52

AWS Big Data

OCTOBER 25, 2023

Most companies produce and consume unstructured data such as documents, emails, web pages, engagement center phone calls, and social media. By some estimates, unstructured data can make up to 80–90% of all new enterprise data and is growing many times faster than structured data.

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Unstructured Data Metadata Management Analytics 117

BizAcuity

MARCH 1, 2019

Data is only useful when it is actionable for which it needs to be supplemented with context and creativity. Traditional methods of analyzing structured data are not designed to efficiently process these large amounts of real-time data that is collected from IoT devices.

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IoT Internet of Things Big Data Data-driven 56

AWS Big Data

DECEMBER 15, 2023

Even after identification, it’s cumbersome to implement redaction, masking, or encryption of sensitive data at scale. In this post, we provide an automated solution to detect PII data in Amazon Redshift using AWS Glue. For our solution, we use Amazon Redshift to store the data.

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Data Lake Data Warehouse Big Data Structured Data 101

AWS Big Data

APRIL 19, 2023

With the right analytics approach, this is possible. 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.

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Data Warehouse Data Lake Unstructured Data Optimization 55

Ontotext

MARCH 8, 2023

Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025, up from 10% in 2021. Graphs boost knowledge discovery and efficient data-driven analytics to understand a company’s relationship with customers and personalize marketing, products, and services.

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Enterprise Knowledge Discovery Risk Data-driven 52

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

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Data Lake Unstructured Data Data Warehouse Data Quality 105

IBM Big Data Hub

APRIL 24, 2023

Benefits of new data warehousing technology Everything is data, regardless of whether it’s structured, semi-structured, or unstructured. Most of the enterprise or legacy data warehousing will support only structured data through relational database management system (RDBMS) databases.

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Data Warehouse Data Lake Cost-Benefit Enterprise 94