Pickl AI

JULY 25, 2024

Data Ingestion Meaning At its core, It refers to the act of absorbing data from multiple sources and transporting it to a destination, such as a database, data warehouse, or data lake. Batch Processing In this method, data is collected over a period and then processed in groups or batches.

Apache Kafka 52

Apache Kafka Data Lakes Data Warehouse Data Quality 52

Alation

AUGUST 4, 2022

Many CIOs argue the rise of big data pushed people to use data more proactively for business decision-making. Big data got“ more leaders and people in the organization to use data, analytics, and machine learning in their decision making,” says former CIO Isaac Sacolick. Big data can grow too big fast.

Big Data 95

Big Data Big Data Apache Kafka Data Lakes 95

Pickl AI

SEPTEMBER 18, 2024

Introduction Netflix has transformed the entertainment landscape, not just through its vast library of content but also by leveraging Big Data across various business verticals. As a pioneer in the streaming industry, Netflix utilises advanced data analytics to enhance user experience, optimise operations, and drive strategic decisions.

Big Data 52

Big Data Big Data Apache Kafka Big Data Analytics 52

Pickl AI

NOVEMBER 4, 2024

Data Engineering is designing, constructing, and managing systems that enable data collection, storage, and analysis. It involves developing data pipelines that efficiently transport data from various sources to storage solutions and analytical tools. ETL is vital for ensuring data quality and integrity.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Pickl AI

JULY 30, 2024

IoT Data Processing With the rise of the Internet of Things (IoT), NiFi is increasingly used to process data generated by IoT devices. It can handle data streams from sensors, perform real-time analytics, and route the data to appropriate storage solutions or analytics platforms.

ETL 52

ETL Data Lakes Big Data Big Data 52

Pickl AI

AUGUST 9, 2024

Summary: A comprehensive Big Data syllabus encompasses foundational concepts, essential technologies, data collection and storage methods, processing and analysis techniques, and visualisation strategies. Velocity It indicates the speed at which data is generated and processed, necessitating real-time analytics capabilities.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

DagsHub

OCTOBER 23, 2024

To combine the collected data, you can integrate different data producers into a data lake as a repository. A central repository for unstructured data is beneficial for tasks like analytics and data virtualization. Data Cleaning The next step is to clean the data after ingesting it into the data lake.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

ODSC - Open Data Science

OCTOBER 9, 2024

What should you be looking for?

Apache Kafka 40

Apache Kafka AI AI Machine Learning 40

Pickl AI

JULY 8, 2024

Definition and Explanation of Data Pipelines A data pipeline is a series of interconnected steps that ingest raw data from various sources, process it through cleaning, transformation, and integration stages, and ultimately deliver refined data to end users or downstream systems.

Data Pipeline 52

Data Pipeline Data Quality Database Apache Kafka 52

Dataconomy

FEBRUARY 23, 2023

Data engineers are responsible for designing and building the systems that make it possible to store, process, and analyze large amounts of data. These systems include data pipelines, data warehouses, and data lakes, among others. However, building and maintaining these systems is not an easy task.

Big Data 91

Big Data Big Data Data Engineering Data Engineering 91

The MLOps Blog

MARCH 15, 2023

Data Processing : You need to save the processed data through computations such as aggregation, filtering and sorting. Data Storage : To store this processed data to retrieve it over time – be it a data warehouse or a data lake.

Data Pipeline 59

Data Pipeline ETL SQL Data Quality 59

ODSC - Open Data Science

MAY 24, 2023

Building a Business with a Real-Time Analytics Stack, Streaming ML Without a Data Lake, and Google’s PaLM 2 Building a Pizza Delivery Service with a Real-Time Analytics Stack The best businesses react quickly and with informed decisions.

Data Lakes 52

Data Lakes ML ML Analytics 52

phData

SEPTEMBER 27, 2024

Technologies like Apache Kafka, often used in modern CDPs, use log-based approaches to stream customer events between systems in real-time. It enables advanced analytics, makes debugging your marketing automations easier, provides natural audit trails for compliance, and allows for flexible, evolving customer data models.

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52