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.

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AWS Big Data

NOVEMBER 15, 2023

BMW Group uses 4,500 AWS Cloud accounts across the entire organization but is faced with the challenge of reducing unnecessary costs, optimizing spend, and having a central place to monitor costs. The ultimate goal is to raise awareness of cloud efficiency and optimize cloud utilization in a cost-effective and sustainable manner.

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Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. Amazon describes the dense storage nodes (DS2) as optimized for large data workloads and use hard disk drives (HDD) for storage.

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CIO Business Intelligence

JUNE 23, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

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Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

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AWS Big Data

MARCH 26, 2024

Profile aggregation – When you’ve uniquely identified a customer, you can build applications in Managed Service for Apache Flink to consolidate all their metadata, from name to interaction history. Then, you transform this data into a concise format. The following screenshot shows an example C360 dashboard built on QuickSight.

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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.

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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.

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AWS Big Data

MARCH 10, 2023

They enable transactions on top of data lakes and can simplify data storage, management, ingestion, and processing. These transactional data lakes combine features from both the data lake and the data warehouse. Data can be organized into three different zones, as shown in the following figure.

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AWS Big Data

SEPTEMBER 13, 2023

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. Moreover, the framework should consume compute resources as optimally as possible per the size of the operational tables.

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Ontotext

FEBRUARY 26, 2024

Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. They have massive amounts of data they’re collecting and storing in their relational databases, document stores, data lakes, and data warehouses. Let’s summarize very quickly.

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AWS Big Data

JANUARY 8, 2024

Kinesis Data Streams has native integrations with other AWS services such as AWS Glue and Amazon EventBridge to build real-time streaming applications on AWS. Refer to Amazon Kinesis Data Streams integrations for additional details. A Lambda function is then invoked with these events, and can perform time series calculations in memory.

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AWS Big Data

MARCH 25, 2024

Streaming jobs constantly ingest new data to synchronize across systems and can perform enrichment, transformations, joins, and aggregations across windows of time more efficiently. It also allows you to transform, enrich, join, and aggregate data across many sources efficiently in near-real time. versions).

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Alation

APRIL 25, 2023

More specifically, it describes the process of creating, administering, and adapting a comprehensive plan for how an organization’s data will be managed. In this way, data governance has implications for a wide range of data management disciplines, including data architecture, quality, security, metadata, and more.

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Alation

APRIL 25, 2023

More specifically, it describes the process of creating, administering, and adapting a comprehensive plan for how an organization’s data will be managed. In this way, data governance has implications for a wide range of data management disciplines, including data architecture, quality, security, metadata, and more.

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AWS Big Data

MARCH 3, 2023

Cost optimization – When you run Spark or Hive applications using EMR Serverless, you pay for the amount of vCPU, memory, and storage resources consumed by your applications, leading to optimal utilization of resources. EMR Serverless includes the Amazon EMR performance-optimized runtime for Apache Spark and Hive.

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IBM Big Data Hub

JANUARY 18, 2023

A read-optimized platform that can integrate data from multiple applications emerged. In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. This storage architecture is inflexible and inefficient. This adds an additional ETL step, making the data even more stale.

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CIO Business Intelligence

MARCH 9, 2022

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. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

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Alation

JANUARY 25, 2022

As a reminder, here’s Gartner’s definition of data fabric: “A design concept that serves as an integrated layer (fabric) of data and connecting processes. In this blog, we will focus on the “integrated layer” part of this definition by examining each of the key layers of a comprehensive data fabric in more detail.

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Alation

APRIL 14, 2022

In today’s AI/ML-driven world of data analytics, explainability needs a repository just as much as those doing the explaining need access to metadata, EG, information about the data being used. The Cloud Data Migration Challenge. A data governance application with the ability to connect to data and security is needed.

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Jet Global

MAY 1, 2023

These sit on top of data warehouses that are strictly governed by IT departments. The role of traditional BI platforms is to collect data from various business systems. Reports In formats that are both static and interactive, these showcase tabular views of data. addresses). Build your first set of reports.

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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.

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IBM Big Data Hub

AUGUST 4, 2023

Today, the way businesses use data is much more fluid; data literate employees use data across hundreds of apps, analyze data for better decision-making, and access data from numerous locations. It uses knowledge graphs, semantics and AI/ML technology to discover patterns in various types of metadata.

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Cloudera

MAY 22, 2019

Although the program is technically in its seventh year, as the first joint awards program, this year’s Data Impact Awards will span even more use cases, covering even more advances in IoT, data warehouse, machine learning, and more. DATA SECURITY AND GOVERNANCE.

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CIO Business Intelligence

AUGUST 3, 2023

It also used device data to develop Lenovo Device Intelligence, which uses AI-driven predictive analytics to help customers understand and proactively prevent and solve potential IT issues. Lenovo Device Intelligence can also help to optimize IT support costs, reduce employee downtime, and improve the user experience, the company says.

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IBM Big Data Hub

JULY 5, 2023

The challenges of a monolithic data lake architecture Data lakes are, at a high level, single repositories of data at scale. Data may be stored in its raw original form or optimized into a different format suitable for consumption by specialized engines.

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