Snowflake

AUGUST 21, 2023

In this blog post, we’ll review the core data mesh principles, highlight how both organizations and modern data platforms are putting those principles into action, and demonstrate just how achievable a secure and efficient data mesh architecture can be.

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Databand.ai

JULY 19, 2023

This capability is useful for businesses, as it provides a clear and comprehensive view of their data’s history and transformations. Data lineage tools are not a new concept. In this article: Why Are Data Lineage Tools Important? One of the unique features of Atlan is its human-centric design.

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Knowledge Hut

NOVEMBER 17, 2023

The demand for data-related professions, including data engineering, has indeed been on the rise due to the increasing importance of data-driven decision-making in various industries. Becoming an Azure Data Engineer in this data-centric landscape is a promising career choice.

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DataKitchen

NOVEMBER 4, 2021

Data organizations often have a mix of centralized and decentralized activity. DataOps concerns itself with the complex flow of data across teams, data centers and organizational boundaries. It expands beyond tools and data architecture and views the data organization from the perspective of its processes and workflows.

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Snowflake

JUNE 28, 2023

Snowpark is our secure deployment and processing of non-SQL code, consisting of two layers: Familiar Client Side Libraries – Snowpark brings deeply integrated, DataFrame-style programming and OSS compatible APIs to the languages data practitioners like to use. Previously, tasks could be executed as quickly as 1-minute.

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Knowledge Hut

SEPTEMBER 26, 2023

Key Features of Azure Synapse Here are some of the key features of Azure Synapse: Cloud Data Service: Azure Synapse operates as a cloud-native service, residing within the Microsoft Azure cloud ecosystem. This cloud-centric approach ensures scalability, flexibility, and cost-efficiency for your data workloads.

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Confluent

JUNE 18, 2019

It involves many moving parts, from data preparation to building indexing and query pipelines. Luckily, this task looks a lot like the way we tackle problems that arise when connecting data. Building an indexing pipeline at scale with Kafka Connect. It is a natural evolution from the initial application-centric setup.

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Monte Carlo

NOVEMBER 10, 2022

That means you have more API integrations and data pipelines that can fail. Often, by the time most marketing teams realize that their knight (the CDP) is a legacy data silo dressed in rusty armor, it’s too late. My guess is that their death will not be quick, but an agonizing slow descent into the oblivion of legacy technology.

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Monte Carlo

JULY 28, 2022

But perhaps one of the most common reasons for data quality challenges are software feature updates and other changes made upstream by software engineers. These are particularly frustrating, because while they are breaking data pipelines constantly, it’s not their fault. What should that solution look like?

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AltexSoft

JULY 18, 2023

Its flexibility allows it to operate on single-node machines and large clusters, serving as a multi-language platform for executing data engineering , data science , and machine learning tasks. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general.

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Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. What is the role of a Data Engineer? Data scientists and data Analysts depend on data engineers to build these data pipelines.

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phData: Data Engineering

JULY 18, 2023

Slow Response to New Information: Legacy data systems often lack the computation power necessary to run efficiently and can be cost-inefficient to scale. This typically results in long-running ETL pipelines that cause decisions to be made on stale or old data.

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Edureka

JULY 4, 2024

Key Advantages of Azure Synapse No Code AI or Analytics Capabilities Azure Synapse takes a significant leap forward in democratizing data analytics and AI by offering robust no-code options. By letting you query data directly in the lake without the need for movement, Synapse cuts down the storage costs and eliminates data duplication.

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Databand.ai

DECEMBER 20, 2022

Neelesh regularly shares his advice channels, including as a recent guest on Databand’s MAD Data Podcast , where he spoke about how engineering can deliver better value for data science. On LinkedIn, he posts frequently about data engineering, data architecture, interview preparation, and career advice.

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