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.

Data Engineer 52

Data Engineer Data Engineering Engineering Scala 52

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.

Python 52

Python Accessible Accessibility Pipeline-centric 52

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.

Process 98

Process Data Process Pharmaceutical Data Lake 98

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?

Software Engineer 52

Software Engineer Software Engineering Pipeline-centric Database-centric 52

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.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

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.

Pipeline-centric 52

Pipeline-centric Data Warehouse Data Cloud Computing 52

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.

Big Data 52

Big Data Data Process Process Hadoop 52

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.

Data Engineer 98

Data Engineer Data Engineering Engineering Pipeline-centric 98

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.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

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.

Data Lake 40

Data Lake Pipeline-centric Data Warehouse ETL Tools 40

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.

Data Analytics 52

Data Analytics Google Cloud Data Science Data Mining 52