Knowledge Hut

JANUARY 18, 2024

“Big data Analytics” is a phrase that was coined to refer to amounts of datasets that are so large traditional data processing software simply can’t manage them. For example, big data is used to pick out trends in economics, and those trends and patterns are used to predict what will happen in the future.

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Data Process Process Hadoop Scala 52

Precisely

JULY 25, 2023

Organizations that run SAP can use Excel-to-SAP automation to do more with less, while also increasing agility and improving their SAP master data management process automation. We bring automation closer to the business users who own the data and the day-to-day processes that drive the business. Check out our free ebook.

Data Process 52

Data Process Process Data Data Integration 52

Data Engineering Podcast

SEPTEMBER 24, 2021

In this episode Ehsan Totoni explains how he built the Bodo project to bring the speed and processing power of HPC techniques to the Python data ecosystem without requiring any re-work. What are the techniques/technologies that teams might use to optimize or scale out their data processing workflows?

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Data Process Python Process Data Lake 100

Data Engineering Podcast

JUNE 9, 2024

Summary Streaming data processing enables new categories of data products and analytics. Unfortunately, reasoning about stream processing engines is complex and lacks sufficient tooling. How has the lack of visibility into the flow of data in Flink impacted the ways that teams think about where/when/how to apply it?

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Process Data Lake High Quality Data Machine Learning 147

Maxime Beauchemin

JANUARY 7, 2018

Batch data processing  — historically known as ETL —  is extremely challenging. In this post, we’ll explore how applying the functional programming paradigm to data engineering can bring a lot of clarity to the process. The greater the claim made using analytics, the greater the scrutiny on the process should be.

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Data Engineer Data Engineering Data Process Process 183

AltexSoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general. GraphX is Spark’s component for processing graph data.

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Big Data Data Process Process Hadoop 52

Snowflake

MARCH 16, 2023

“Ownership was difficult because we had replicas of the data everywhere, which meant we didn’t really know who to speak to about the different data sets. A lack of data standardization from disconnected processes also posed a potential risk for John Lewis. “We Governing it was overly onerous.”

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Data Process Cloud Process IT 52

DoorDash Engineering

NOVEMBER 21, 2022

While building out DashMart’s internal inventory management system to help DashMart associates manage inventory, the DashMart engineering team came to realize that since the inventory tables were so core and foundational to different operational use cases in a DashMart, some actions or code must be triggered every time the inventory level changes.

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Data Process Process Kafka Database 57

LinkedIn Engineering

OCTOBER 19, 2023

Authors: Bingfeng Xia and Xinyu Liu Background At LinkedIn, Apache Beam plays a pivotal role in stream processing infrastructures that process over 4 trillion events daily through more than 3,000 pipelines across multiple production data centers.

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Process Lambda Architecture Kafka Machine Learning 119

Striim

NOVEMBER 17, 2023

Striim serves as a real-time data integration platform that seamlessly and continuously moves data from diverse data sources to destinations such as cloud databases, messaging systems, and data warehouses, making it a vital component in modern data architectures.

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Machine Learning Data Process PostgreSQL Process 52

Data Engineering Podcast

NOVEMBER 27, 2022

This has led to inefficiencies in how data is stored, accessed, and shared across process and system boundaries. The Arrow project is designed to eliminate wasted effort in translating between languages, and Voltron Data was created to help grow and support its technology and community.

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Data Process Process Metadata Business Intelligence 100

phData: Data Engineering

NOVEMBER 8, 2024

The world we live in today presents larger datasets, more complex data, and diverse needs, all of which call for efficient, scalable data systems. Open Table Format (OTF) architecture now provides a solution for efficient data storage, management, and processing while ensuring compatibility across different platforms.

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Architecture Systems Data Lake Google Cloud 52

Netflix Tech

MARCH 7, 2024

The Machine Learning Platform (MLP) team at Netflix provides an entire ecosystem of tools around Metaflow , an open source machine learning infrastructure framework we started, to empower data scientists and machine learning practitioners to build and manage a variety of ML systems.

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Systems Media Machine Learning Data Warehouse 93

Towards Data Science

APRIL 30, 2024

Balancing correctness, latency, and cost in unbounded data processing Image created by the author. Intro Google Dataflow is a fully managed data processing service that provides serverless unified stream and batch data processing. Apache Beam lets users define processing logic based on the Dataflow model.

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Google Cloud Process Cloud Lambda Architecture 60

ProjectPro

JANUARY 25, 2022

PySpark is a handy tool for data scientists since it makes the process of converting prototype models into production-ready model workflows much more effortless. PySpark is used to process real-time data with Kafka and Streaming, and this exhibits low latency. RDD uses a key to partition data into smaller chunks.

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Big Data Data Process Process Kafka 52

Towards Data Science

FEBRUARY 18, 2024

How to Stream and Apply Real-Time Prediction Models on High-Throughput Time-Series Data Photo by JJ Ying on Unsplash Most of the stream processing libraries are not python friendly while the majority of machine learning and data mining libraries are python based. This design enables the re-reading of old messages.

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Kafka Python Process Google Cloud 76

Data Engineering Podcast

DECEMBER 31, 2018

Summary As more companies and organizations are working to gain a real-time view of their business, they are increasingly turning to stream processing technologies to fullfill that need. However, the storage requirements for continuous, unbounded streams of data are markedly different than that of batch oriented workloads.

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Lambda Architecture Process Data Process Kafka 100

Striim

JULY 30, 2024

Ensuring system resilience is critical for maintaining a competitive edge in today’s data-driven world. As businesses rely on real-time data to fuel decision-making, it’s essential that their systems can withstand disruptions and maintain functionality. Check out this blog.) Here’s how it works.

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Systems Healthcare Utilities Data Integration 52

Precisely

OCTOBER 2, 2023

Manual, error-prone SAP data processes simply don’t cut it anymore. Automating the processes that create and maintain the vast amounts of interdependent data that support your SAP ERP business processes is key to gaining agility, speed, and improved data quality and integrity. Automation.

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Process Finance Government Data Management 64

Netflix Tech

AUGUST 1, 2022

Data Mesh?—?A A Data Movement and Processing Platform @ Netflix By Bo Lei , Guilherme Pires , James Shao , Kasturi Chatterjee , Sujay Jain , Vlad Sydorenko Background Realtime processing technologies (A.K.A This article gives an overview of the system. It contains a reusable unit of data processing logic.

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Process Transportation Kafka Entertainment 109

Precisely

JANUARY 31, 2024

As this drive toward increased efficiency and agility continues, here are the trends that we see unfolding in 2024 for automating SAP processes. Simply put: manual, error-prone processes simply don’t cut it anymore if you want to survive and thrive in a fast-paced digital landscape. This process is notoriously complex and error-prone.

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Process Data Validation Algorithm Technology 59

Data Engineering Podcast

NOVEMBER 20, 2021

With the improvements in streaming engines it is now possible to perform all of your data integration in near real time, but it can be challenging to understand the proper processing patterns to make that performant. Can you start by giving an overview of the state of the market for data lakes today?

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Data Lake Data Integration Lambda Architecture Process 100

Data Science Blog: Data Engineering

NOVEMBER 15, 2023

In addition to Business Intelligence (BI), Process Mining is no longer a new phenomenon, but almost all larger companies are conducting this data-driven process analysis in their organization. This aspect can be applied well to Process Mining, hand in hand with BI and AI.

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Architecture Database-centric Process BI 52

Data Engineering Podcast

JULY 27, 2020

Summary A majority of the scalable data processing platforms that we rely on are built as distributed systems. Kyle Kingsbury created the Jepsen framework for testing the guarantees of distributed data processing systems and identifying when and why they break.

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Systems Building Scala Java 100

Data Engineering Podcast

APRIL 24, 2022

WhyLogs is a powerful library for flexibly instrumenting all of your data systems to understand the entire lifecycle of your data from source to productionized model. You have full control over your data and their plugin system lets you integrate with all of your other data tools, including data warehouses and SaaS platforms.

Machine Learning 100

Machine Learning Systems Data Lake Java 100

Rockset

DECEMBER 19, 2023

From his early days at Quora to leading projects at Facebook and his current venture at Fennel (a real-time feature store for ML), Nikhil has traversed the evolving landscape of machine learning engineering and machine learning infrastructure specifically in the context of recommendation systems.

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Systems Machine Learning Deep Learning Media 52

Start Data Engineering

MAY 28, 2024

Building efficient data pipelines with DuckDB 4.1. Use DuckDB to process data, not for multiple users to access data 4.2. Cost calculation: DuckDB + Ephemeral VMs = dirt cheap data processing 4.3. Processing data less than 100GB? Project demo 3. Use DuckDB 4.4.

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Data Pipeline Python Building Data 219

Cloudera

SEPTEMBER 11, 2018

The open data processing pipeline. IoT is expected to generate a volume and variety of data greatly exceeding what is being experienced today, requiring modernization of information infrastructure to realize value. Telemetry data routed to the Cloudera Enterprise Data Hub flows into Apache Kafka.

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Data Process Process Building Machine Learning 40

ProjectPro

FEBRUARY 16, 2023

With its easy-to-use interface and robust features, OpenCV has become the favorite of data scientists and computer vision engineers. Whether you’re looking to track objects in a video stream, build a face recognition system, or edit images creatively, OpenCV Python implementation is the go-to choice for the job.

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Python Process Deep Learning Algorithm 98

Precisely

AUGUST 10, 2023

Data integrity : Leaders also recognize the need to improve the quality and integrity of their most important data. For many organizations, that means paying considerable attention to SAP master data and the processes for creating and managing that information.

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Process Data Integration Manufacturing Portfolio 52

Knowledge Hut

JANUARY 30, 2024

ITIL Processes ITIL comprises several processes that make it extremely adaptable, scalable, and diverse. These processes consist of activities with specified inputs, causes, and outputs. Let's look at some of the ITIL Processes and ideas that underpin them. This process is completed through five successive activities.

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Process Certification Portfolio Accessible 52

LinkedIn Engineering

MARCH 23, 2023

Co-Authors: Yuhong Cheng , Shangjin Zhang , Xinyu Liu, and Yi Pan Efficient data processing is crucial in reducing learning curves, simplifying maintenance efforts, and decreasing operational complexity. By unifying these pipelines, we have saved 94% of processing time. Samza , Spark and Apache Flink ).

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Process Lambda Architecture Kafka Datasets 97

Towards Data Science

FEBRUARY 9, 2024

This involves getting data from an API and storing it in a PostgreSQL database. This first part project is ideal for beginners in data engineering, as well as for data scientists and machine learning engineers looking to deepen their knowledge of the entire data handling process. Overview of the data pipeline.

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Kafka Data Engineer Data Engineering PostgreSQL 72

Knowledge Hut

JULY 24, 2023

The future of SQL (Structured Query Language) is a scalding subject among professionals in the data-driven world. As data generation continues to skyrocket, the demand for real-time decision-making, data processing, and analysis increases. It is also integrable with other programming languages like Python and R.

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Database SQL Process NoSQL 52

Knowledge Hut

JANUARY 23, 2024

To stay on top of processes and synchronize all the elements involved, I turn to one of the key best practices in the rule book: Project Integration Management. Here’s what can be achieved through integration management: Processes and tasks can be organized and listed out. Get to know more about project description.

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Project Process Management Certification 52

Precisely

FEBRUARY 27, 2023

Data is the fuel that drives business decisions in today’s world. To use it effectively, organizations must invest in the people, processes, and technology that enable users throughout the organization to make sound business decisions based on trusted data. That includes making a firm commitment to business agility.

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Process Finance Datasets Designing 52

Rockset

MARCH 28, 2024

Find an end-to-end Colab notebook that you can run without any dependencies on your local operating system: Recsys_workshop. Introduction A real-time personalized recommender system can add tremendous value to an organization by enhancing the level user engagement and ultimately increasing user satisfaction.

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Systems Building Database Utilities 52