Edureka

AUGUST 2, 2023

Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly. Data processing analysts can be useful in this situation. Let’s take a deep dive into the subject and look at what we’re about to study in this blog: Table of Contents What Is Data Processing Analysis?

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Data Process Process Data Cleanse Data Mining 52

Snowflake

MARCH 16, 2023

It needed to unite its data silos to give its customer, trading, and operational teams timely and robust insight to drive informed strategic decisions. Find out why its Chief Data and Insight Officer chose Snowflake as its unifying data platform—and how it’s given the partnership greater control over its data.

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Data Process Cloud Process IT 52

DataKitchen

NOVEMBER 4, 2021

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. One data engineer called it the “last mile problem.” .

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Cloudyard

FEBRUARY 19, 2024

Read Time: 1 Minute, 42 Second In this blog post, we’ll delve into a practical example that showcases the prowess of Snowpark by processing customer invoice data from a CSV file and handling credit card details from a JSON source. The journey begins with customer invoice data stored in a CSV file.

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Data Engineering Podcast

FEBRUARY 20, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. for abstracting over the execution engine?

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Python Data Process IT Building 100

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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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.

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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

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

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. Data observability has been gaining adoption for a number of years now, with a large focus on data warehouses.

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Process Data Lake High Quality Data Machine Learning 147

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. Maintained by the Apache Software Foundation, Apache Spark is an open-source, unified engine designed for large-scale data analytics. What is Apache Spark?

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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

Hevo

APRIL 26, 2024

Most organizations find it challenging to manage data from diverse sources efficiently. However, simply storing the data isn’t enough. To drive your business growth, you need to analyze this data to […]

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AWS Amazon Web Services Data Process 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

DoorDash Engineering

NOVEMBER 21, 2022

Subscribe for weekly updates The solution to real-time processing of inventory changes The simplest approach to propagating inventory level changes in the database to the rest of the system may have been to invoke the service code to take actions every time something that affects the inventory table is called.

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Data Process Process Kafka Database 57

Simon Späti

MARCH 8, 2023

Thankfully, a widely used Python library known as Pandas has become the go-to tool for processing and manipulating data. Pandas has established itself as the standard tool for in-memory data processing in Python, and it offers an extensive range of data manipulation capabilities.

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IT Python Datasets Data Engineer 130

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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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. Another reason to use PySpark is that it has the benefit of being able to scale to far more giant data sets compared to the Python Pandas library. Why use PySpark?

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Big Data Data Process Process Kafka 52

Ascend.io

JULY 11, 2024

Metadata is the information that provides context and meaning to data, ensuring it’s easily discoverable, organized, and actionable. It enhances data quality, governance, and automation, transforming raw data into valuable insights. This is what managing data without metadata feels like. Chaos, right?

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Metadata IT Government High Quality Data 52

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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Precisely

FEBRUARY 29, 2024

Complexity is at the core of SAP automation challenges The core challenges to automating SAP processes essentially boil down to complexity. The business processes themselves are complex, as are the data objects associated with each SAP record. Let’s start with the complexity of the business processes.

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IT Process Data Collection Data Process 59

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.

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Kafka Python Process Google Cloud 75

ThoughtSpot

OCTOBER 18, 2024

In the fast-paced world of software development, the efficiency of build processes plays a crucial role in maintaining productivity and code quality. This requirement prompted us to explore Build Analytics—harnessing data from our build processes to gain actionable insights.

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DareData

MARCH 30, 2022

Many times, a data developer is constrained by the data they were given. In Data Science / Engineering projects, it is not unusual that extra data is added from other sources - even ones that are outside of the organization. But extra data can be available in non-standard ways, that require new processing techniques.

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Process IT Hospitality Data 52

Netflix Tech

NOVEMBER 20, 2023

by Jun He , Yingyi Zhang , and Pawan Dixit Incremental processing is an approach to process new or changed data in workflows. The key advantage is that it only incrementally processes data that are newly added or updated to a dataset, instead of re-processing the complete dataset.

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Process Data Pipeline Datasets SQL 86

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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Cloudera

MARCH 2, 2023

Iceberg is a high-performance open table format for huge analytic data sets. It allows multiple data processing engines, such as Flink, NiFi, Spark, Hive, and Impala to access and analyze data in simple, familiar SQL tables. This enables you to maximize utilization of streaming data at scale. Try it out yourself!

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Process SQL Kafka Database 112

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

Precisely

JANUARY 31, 2024

SAP does a great job managing all of that complexity, but it takes many resources to maintain master data, update SAP information on a timely basis, and keep everything running smoothly. As this drive toward increased efficiency and agility continues, here are the trends that we see unfolding in 2024 for automating SAP processes.

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Snowflake

MARCH 14, 2024

Along with SNP Glue, the Snowflake Native App gives customers a simple, flexible and cost-effective solution to get data out of SAP and into Snowflake quickly and accurately. What’s the challenge with unlocking SAP data? Getting direct access to SAP data is critical because it holds such a breadth of ERP information.

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IT Data Ingestion Data AWS 97

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 Last year we wrote a blog post about how Data Mesh helped our Studio team enable data movement use cases.

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Process Transportation Kafka Entertainment 109

Data Engineering Weekly

DECEMBER 2, 2023

AWS S3 Express One Zone sparks some delight in the data infrastructure. link] Amazon S3 Express One Zone is a high-performance, single-availability Zone storage class purpose-built to deliver consistent single-digit millisecond data access for your most frequently accessed data and latency-sensitive applications.

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IT BI AWS Kafka 85

KDnuggets

JANUARY 18, 2022

TLDR; process it with a new Python Data Processing Engine in the Cloud.

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Process Python Cloud Data Process 158

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

Cloudera

SEPTEMBER 11, 2018

Last week Cloudera introduced an open end-to-end architecture for IoT and the different components needed to help satisfy today’s enterprise needs regarding operational technology (OT), information technology (IT), data analytics and machine learning (ML), along with modern and traditional application development, deployment, and integration.

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Data Process Process Building Machine Learning 40

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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LinkedIn Engineering

JUNE 15, 2023

However, we found that many of our workloads were bottlenecked by reading multiple terabytes of input data. To remove this bottleneck, we built AvroTensorDataset , a TensorFlow dataset for reading, parsing, and processing Avro data. an array within a map, within a union, etc…). drop_remainder tf.bool (Optional.)

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