Smart Data Collective

SEPTEMBER 26, 2019

The big data market is expected to be worth $189 billion by the end of this year. A number of factors are driving growth in big data. Demand for big data is part of the reason for the growth, but the fact that big data technology is evolving is another. Characteristics of Big Data.

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O'Reilly Media

SEPTEMBER 19, 2023

Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” ” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize.

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Pickl AI

DECEMBER 2, 2024

Summary: Big Data encompasses vast amounts of structured and unstructured data from various sources. Key components include data storage solutions, processing frameworks, analytics tools, and governance practices. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

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Pickl AI

NOVEMBER 25, 2024

Summary: Big Data encompasses vast amounts of structured and unstructured data from various sources. Key components include data storage solutions, processing frameworks, analytics tools, and governance practices. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

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Flipboard

NOVEMBER 17, 2023

Generative AI models have the potential to revolutionize enterprise operations, but businesses must carefully consider how to harness their power while overcoming challenges such as safeguarding data and ensuring the quality of AI-generated content. As a Data Engineer he was involved in applying AI/ML to fraud detection and office automation.

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Alation

FEBRUARY 20, 2020

Architecturally the introduction of Hadoop, a file system designed to store massive amounts of data, radically affected the cost model of data. Organizationally the innovation of self-service analytics, pioneered by Tableau and Qlik, fundamentally transformed the user model for data analysis. Disruptive Trend #1: Hadoop.

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DagsHub

DECEMBER 11, 2023

LakeFS Most big data storage solutions such as Azure, Google cloud storage, and Amazon S3 have good performance, cost-effective, and have good connectivity with other tooling. However, these tools have functional gaps for more advanced data workflows. Git LFS requires a LFS server to work.

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AWS Machine Learning Blog

DECEMBER 18, 2023

In this post, we will explore the potential of using MongoDB’s time series data and SageMaker Canvas as a comprehensive solution. MongoDB Atlas MongoDB Atlas is a fully managed developer data platform that simplifies the deployment and scaling of MongoDB databases in the cloud.

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Pickl AI

JULY 10, 2023

As a programming language it provides objects, operators and functions allowing you to explore, model and visualise data. The programming language can handle Big Data and perform effective data analysis and statistical modelling.

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Pickl AI

NOVEMBER 28, 2024

Knowledge of Cloud Computing and Big Data Tools As complex Machine Learning (ML) models grow, robust infrastructure for large datasets and intensive computations becomes increasingly important. Big Data Tools Integration Big data tools like Apache Spark and Hadoop are vital for managing and processing massive datasets.

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Pickl AI

OCTOBER 10, 2024

Enhanced Data Quality : These tools ensure data consistency and accuracy, eliminating errors often occurring during manual transformation. Scalability : Whether handling small datasets or processing big data, transformation tools can easily scale to accommodate growing data volumes.

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DagsHub

OCTOBER 23, 2024

Data Preprocessing Here, you can process the unstructured data into a format that can be used for the other downstream tasks. For instance, if the collected data was a text document in the form of a PDF, the data preprocessing—or preparation stage —can extract tables from this document. Unstructured.io

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Pickl AI

JUNE 7, 2024

Open-Source Community: Airflow benefits from an active open-source community and extensive documentation. IBM Infosphere DataStage IBM Infosphere DataStage is an enterprise-level ETL tool that enables users to design, develop, and run data pipelines. Read More: Advanced SQL Tips and Tricks for Data Analysts.

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Pickl AI

AUGUST 21, 2024

Apache Nutch A powerful web crawler built on Apache Hadoop, suitable for large-scale data crawling projects. It is designed for scalability and can handle vast amounts of data. Nutch is often used in conjunction with other Hadoop tools for big data processing.

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Pickl AI

APRIL 2, 2024

Understanding Data Structured Data: Organized data with a clear format, often found in databases or spreadsheets. Unstructured Data: Data without a predefined structure, like text documents, social media posts, or images. Hadoop/Spark: Frameworks for distributed storage and processing of big data.

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Pickl AI

DECEMBER 4, 2024

This explosive growth is driven by the increasing volume of data generated daily, with estimates suggesting that by 2025, there will be around 181 zettabytes of data created globally. The field has evolved significantly from traditional statistical analysis to include sophisticated Machine Learning algorithms and Big Data technologies.

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Pickl AI

JANUARY 28, 2025

External Data Sources: These can be market research data, social media feeds, or third-party databases that provide additional insights. Data can be structured (e.g., documents and images). The diversity of data sources allows organizations to create a comprehensive view of their operations and market conditions.

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Mlearning.ai

JULY 10, 2023

In my 7 years of Data Science journey, I’ve been exposed to a number of different databases including but not limited to Oracle Database, MS SQL, MySQL, EDW, and Apache Hadoop. link] Tables The table in GCP BigQuery is a collection of rows and columns that can store and manage massive amounts of data.

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DagsHub

NOVEMBER 11, 2024

So, we must understand the different unstructured data types and effectively process them to uncover hidden patterns. Textual Data Textual data is one of the most common forms of unstructured data and can be in the format of documents, social media posts, emails, web pages, customer reviews, or conversation logs.

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phData

OCTOBER 20, 2023

To support these diverse data sources, semi-structured data formats have become popular standards for transporting and storing data. What are Supported File Formats for Semi-structured Data Various semi-structured datasets, including JSON, Avro, Parquet, Orc, and XML, have emerged with the rise of big data and IoT.

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Pickl AI

MAY 31, 2023

Accordingly, it is possible for the Python users to ask for help from Stack Overflow, mailing lists and user-contributed code and documentation. Tools such as Matplotlib, Seaborn, and Tableau may help you in creating useful visualisations that make challenging data more readily available and understandable to others.

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ODSC - Open Data Science

JANUARY 7, 2025

Classification techniques, such as image recognition and document categorization, remain essential for a wide range of industries. Soft Skills Technical expertise alone isnt enough to thrive in the evolving data science landscape. Employers increasingly seek candidates with strong soft skills that complement technical prowess.

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Pickl AI

MAY 15, 2023

The type of data processing enables division of data and processing tasks among the multiple machines or clusters. Distributed processing is commonly in use for big data analytics, distributed databases and distributed computing frameworks like Hadoop and Spark.

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DagsHub

AUGUST 23, 2024

It integrates well with modern data engineering pipelines (e.g., Airflow, dbt) and automatically generates documentation based on the set expectations. Pandera is an open-source data validation tool built on top of Pandas. It allows users to define, measure, monitor, and validate data quality.

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