Smart Data Collective

OCTOBER 17, 2022

Big data is shaping our world in countless ways. Data powers everything we do. Exactly why, the systems have to ensure adequate, accurate and most importantly, consistent data flow between different systems. There are a number of challenges in data storage , which data pipelines can help address.

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Adrian Bridgwater for Forbes

JUNE 15, 2023

We can also use AI to perform lower-level software & data system functions that users will be mostly oblivious to to make make users' apps & services work correctly.

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Smart Data Collective

JULY 26, 2020

Data pipelines have been crucial for brands in a number of ways. In March, Hubspot talked about the shift towards incorporating big data into marketing pipelines in B2B campaigns. “A However, it is important to use the right data pipelines to leverage these benefits.

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Smart Data Collective

SEPTEMBER 19, 2022

Big data has led to many important breakthroughs in the Fintech sector. And Big Data is one such excellent opportunity ! Big Data is the collection and processing of huge volumes of different data types, which financial institutions use to gain insights into their business processes and make key company decisions.

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Smart Data Collective

DECEMBER 28, 2022

A data pipeline is a technical system that automates the flow of data from one source to another. While it has many benefits, an error in the pipeline can cause serious disruptions to your business. Here are some of the best practices for preventing errors in your data pipeline: 1. Monitor Your Data Sources.

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Pickl AI

APRIL 21, 2025

Summary: Big Data refers to the vast volumes of structured and unstructured data generated at high speed, requiring specialized tools for storage and processing. Data Science, on the other hand, uses scientific methods and algorithms to analyses this data, extract insights, and inform decisions.

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Dataconomy

MAY 26, 2017

Amazon Kinesis is a platform to build pipelines for streaming data at the scale of terabytes per hour. The post Amazon Kinesis vs. Apache Kafka For Big Data Analysis appeared first on Dataconomy. Parts of the Kinesis platform are.

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Adrian Bridgwater for Forbes

OCTOBER 16, 2023

As we create a new world of massive data, we may need a new approach to data pipeline maintenance if we are going to be able to keep the flow flowing.

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Dataconomy

JUNE 12, 2025

Responsibilities of a data engineer The responsibilities of a data engineer can be extensive. They are primarily tasked with the creation and maintenance of robust data pipelines that ensure seamless data flow from source to destination.

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Women in Big Data

FEBRUARY 27, 2025

Big data pipelines are the backbone of modern data processing, enabling organizations to collect, process, and analyze vast amounts of data in real-time. Issues such as data inconsistencies, performance bottlenecks, and failures are inevitable.In Validate data format and schema compatibility.

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Hacker News

APRIL 26, 2024

Using Iceberg allows us to pick the optimal "big data" compute environment for the specific requirements we have. There's no need to limit yourself to a single solution.

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Dataconomy

JUNE 18, 2025

Extract, Transform, Load (ETL) The ETL process involves extracting data from various sources, transforming it into a suitable format, and loading it into data warehouses, typically utilizing batch processing. This approach allows organizations to work with large volumes of data efficiently.

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Precisely

DECEMBER 28, 2023

Business success is based on how we use continuously changing data. That’s where streaming data pipelines come into play. This article explores what streaming data pipelines are, how they work, and how to build this data pipeline architecture. What is a streaming data pipeline?

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Data Science Dojo

JULY 6, 2023

Data engineering tools are software applications or frameworks specifically designed to facilitate the process of managing, processing, and transforming large volumes of data. It integrates seamlessly with other AWS services and supports various data integration and transformation workflows.

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Dataconomy

FEBRUARY 23, 2023

Data engineers play a crucial role in managing and processing big data. They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. They must also ensure that data privacy regulations, such as GDPR and CCPA , are followed.

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IBM Journey to AI blog

AUGUST 12, 2024

Driven by significant advancements in computing technology, everything from mobile phones to smart appliances to mass transit systems generate and digest data, creating a big data landscape that forward-thinking enterprises can leverage to drive innovation. However, the big data landscape is just that.

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ODSC - Open Data Science

JUNE 19, 2023

With the advent of big data in the modern world, RTOS is becoming increasingly important. As software expert Tim Mangan explains, a purpose-built real-time OS is more suitable for apps that involve tons of data processing. The Big Data and RTOS connection IoT and embedded devices are among the biggest sources of big data.

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Dataversity

DECEMBER 14, 2020

It was only a few years ago that BI and data experts excitedly claimed that petabytes of unstructured data could be brought under control with data pipelines and orderly, efficient data warehouses. But as big data continued to grow and the amount of stored information increased every […].

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Women in Big Data

OCTOBER 9, 2024

With the explosive growth of big data over the past decade and the daily surge in data volumes, it’s essential to have a resilient system to manage the vast influx of information without failures. The success of any data initiative hinges on the robustness and flexibility of its big data pipeline.

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Dataconomy

APRIL 3, 2025

He spearheads innovations in distributed systems, big-data pipelines, and social media advertising technologies, shaping the future of marketing globally. Here, he was pivotal in building scalable, high-impact systems that leverage big-data processing and machine learning. His work today reflects this vision.

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Dataconomy

JUNE 19, 2025

Distinction between data architect and data engineer While there is some overlap between the roles, a data architect typically focuses on setting high-level data policies. In contrast, data engineers are responsible for implementing these policies through practical database designs and data pipelines.

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Flipboard

NOVEMBER 7, 2023

“Data is at the center of every application, process, and business decision,” wrote Swami Sivasubramanian, VP of Database, Analytics, and Machine Learning at AWS, and I couldn’t agree more. A common pattern customers use today is to build data pipelines to move data from Amazon Aurora to Amazon Redshift.

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IBM Data Science in Practice

APRIL 7, 2025

Graceful External Termination: Handling Pod Deletions in Kubernetes Data Ingestion and Streaming Jobs When running big-data pipelines in Kubernetes, especially streaming jobs, its easy to overlook how these jobs deal with termination. What happens when a user or system administrator needs to kill a job mid-execution?

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Adrian Bridgwater for Forbes

MARCH 7, 2024

A data fabric is textured approach to combining disparate data sources, data pipelines, databases, data streams and cloud data services into one woven unified entity.

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Pickl AI

DECEMBER 9, 2024

Summary: This article provides a comprehensive guide on Big Data interview questions, covering beginner to advanced topics. Introduction Big Data continues transforming industries, making it a vital asset in 2025. The global Big Data Analytics market, valued at $307.51 What is Big Data?

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Smart Data Collective

SEPTEMBER 23, 2020

While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes. Both data warehouses and data lakes are used when storing big data.

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Pickl AI

DECEMBER 26, 2024

Summary: “Data Science in a Cloud World” highlights how cloud computing transforms Data Science by providing scalable, cost-effective solutions for big data, Machine Learning, and real-time analytics. This accessibility democratises Data Science, making it available to businesses of all sizes.

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Women in Big Data

NOVEMBER 27, 2024

Optimized for analytical processing, it uses specialized data models to enhance query performance and is often integrated with business intelligence tools, allowing users to create reports and visualizations that inform organizational strategies. architecture for both structured and unstructured data.

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Pickl AI

DECEMBER 26, 2024

Summary: Big Data revolutionises promotional strategies by enabling personalised, data-driven marketing campaigns. Businesses leveraging Big Data effectively gain a competitive edge in connecting with audiences and optimising campaign performance while fostering trust through responsible data use.

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Pickl AI

MARCH 19, 2025

Summary: Data engineering tools streamline data collection, storage, and processing. Learning these tools is crucial for building scalable data pipelines. offers Data Science courses covering these tools with a job guarantee for career growth. Below are 20 essential tools every data engineer should know.

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Flipboard

NOVEMBER 27, 2024

While customers can perform some basic analysis within their operational or transactional databases, many still need to build custom data pipelines that use batch or streaming jobs to extract, transform, and load (ETL) data into their data warehouse for more comprehensive analysis. Choose Delete stack.

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Adrian Bridgwater for Forbes

DECEMBER 1, 2022

What businesses need from cloud computing is the power to work on their data without having to transport it around between different clouds, different databases and different repositories, different integrations to third-party applications, different data pipelines and different compute engines.

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Flipboard

MARCH 3, 2023

Data proliferation has become a norm and as organizations become more data driven, automating data pipelines that enable data ingestion, curation, …

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Flipboard

JUNE 18, 2025

As always, enterprises need to know their data pipeline so they can compare the performance of the agents they are monitoring. What do they need the AI application or agents to do, and how are these planned to support their work?

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Data Science Dojo

APRIL 16, 2024

Big data engineer Potential pay range – US$206,000 to 296,000/yr They operate at the backend to build and maintain complex systems that store and process the vast amounts of data that fuel AI applications. With the growing amount of data for businesses, the demand for big data engineers is only bound to grow in 2024.

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Smart Data Collective

OCTOBER 17, 2022

While growing data enables companies to set baselines, benchmarks, and targets to keep moving ahead, it poses a question as to what actually causes it and what it means to your organization’s engineering team efficiency. What’s causing the data explosion? Big data analytics from 2022 show a dramatic surge in information consumption.

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Smart Data Collective

APRIL 2, 2019

These massive storage pools of data are among the most non-traditional methods of data storage around and they came about as companies raced to embrace the trend of Big Data Analytics which was sweeping the world in the early 2010s. Big Data is, well…big.

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