AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

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AWS Big Data

FEBRUARY 13, 2023

This is a guest post by Miguel Chin, Data Engineering Manager at OLX Group and David Greenshtein, Specialist Solutions Architect for Analytics, AWS. We live in a data-producing world, and as companies want to become data driven, there is the need to analyze more and more data.

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Snapshot Data Warehouse Testing Analytics 69

Sisense

JANUARY 6, 2020

Best practice blends the application of advanced data models with the experience, intuition and knowledge of sales management, to deeply understand the sales pipeline. For this partnership to work, it requires sales leaders who really care about data and are open to analysts’ advice about how to use the Salesforce data they generate.

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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. In this post, we discuss a common use case in relation to operational data processing and the solution we built using Apache Hudi and AWS Glue.

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AWS Big Data

MAY 10, 2023

In OpenSearch Service, you can deploy data nodes to store your data and respond to indexing and search requests, you can also deploy dedicated cluster manager nodes to manage and orchestrate the cluster. When you use OpenSearch Service, you create indexes to hold your data and specify partitioning and replication for those indexes.

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AWS Big Data

JANUARY 27, 2023

To build a data-driven business, it is important to democratize enterprise data assets in a data catalog. With a unified data catalog, you can quickly search datasets and figure out data schema, data format, and location. For metadata read/write, Flink has the catalog interface.

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Data Lake Metadata Business Analysis Data-driven 63

Alation

AUGUST 26, 2021

What Is Data Intelligence? Data intelligence is a system to deliver trustworthy, reliable data. It includes intelligence about data, or metadata. IDC coined the term, stating, “data intelligence helps organizations answer six fundamental questions about data.” Why do we have data?

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Cloudera

MARCH 15, 2023

In this post, I will demonstrate how to use the Cloudera Data Platform (CDP) and its streaming solutions to set up reliable data exchange in modern applications between high-scale microservices, and ensure that the internal state will stay consistent even under the highest load.

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Alation

JULY 28, 2022

There was a time when most CIOs would never consider putting their crown jewels — AKA customer data and associated analytics — into the cloud. And what must organizations overcome to succeed at cloud data warehousing ? What Are the Biggest Drivers of Cloud Data Warehousing? The cloud is no longer synonymous with risk.

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Data Warehouse Cost-Benefit Data Governance Data-driven 69

AWS Big Data

MARCH 25, 2024

FMs are multimodal; they work with different data types such as text, video, audio, and images. Large language models (LLMs) are a type of FM and are pre-trained on vast amounts of text data and typically have application uses such as text generation, intelligent chatbots, or summarization.

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AWS Big Data

JANUARY 17, 2024

This allows you to simplify security and governance over transactional data lakes by providing access controls at table-, column-, and row-level permissions with your Apache Spark jobs. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

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Data Lake Snapshot Big Data Data-driven 96

DataKitchen

JANUARY 23, 2023

What is data lineage? Data lineage traces data’s origin, history, and movement through various processing, storage, and analysis stages. It is used to understand the provenance of data and how it is transformed and to identify potential errors or issues. What about DataOps Observability? How does it compare?

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