Data Science Dojo

SEPTEMBER 11, 2024

With this full-fledged solution, you don’t have to spend all your time and effort combining different services or duplicating data. Overview of One Lake Fabric features a lake-centric architecture, with a central repository known as OneLake. Here, we changed the data types of columns and dealt with missing values.

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AWS Machine Learning Blog

AUGUST 8, 2024

Data is the foundational layer for all generative AI and ML applications. Managing and retrieving the right information can be complex, especially for data analysts working with large data lakes and complex SQL queries. The following diagram illustrates the solution architecture.

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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. million in 2024 and is projected to grow at a CAGR of 26.8%

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AWS Machine Learning Blog

NOVEMBER 12, 2024

Focused on addressing the challenge of agricultural data standardization, Agmatix has developed proprietary patented technology to harmonize and standardize data, facilitating informed decision-making in agriculture. Multi-source data is initially received and stored in an Amazon Simple Storage Service (Amazon S3) data lake.

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AWS Machine Learning Blog

OCTOBER 24, 2024

RAG introduces an information retrieval component that uses the user input to first pull information from a new data source. This new data from outside of the LLM’s original training data set is called external data. The data might exist in various formats such as files, database records, or long-form text.

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ODSC - Open Data Science

JANUARY 30, 2024

Not only does it involve the process of collecting, storing, and processing data so that it can be used for analysis and decision-making, but these professionals are responsible for building and maintaining the infrastructure that makes this possible; and so much more. Think of data engineers as the architects of the data ecosystem.

Data Engineering 52

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DagsHub

OCTOBER 23, 2024

How to leverage Generative AI to manage unstructured data Benefits of applying proper unstructured data management processes to your AI/ML project. What is Unstructured Data? One thing is clear : unstructured data doesn’t mean it lacks information.

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DagsHub

DECEMBER 11, 2023

Data auditing and compliance Almost each company face data protection regulations such as GDPR, forcing them to store certain information in order to demonstrate compliance and history of data sources. In this scenario, data versioning can help companies in both internal and external audits process.

Machine Learning 98

Machine Learning Machine Learning Data Lakes Database 98

Smart Data Collective

AUGUST 17, 2022

You can safely use an Apache Kafka cluster for seamless data movement from the on-premise hardware solution to the data lake using various cloud services like Amazon’s S3 and others. It will enable you to quickly transform and load the data results into Amazon S3 data lakes or JDBC data stores.

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Dataversity

JANUARY 25, 2023

Over the past few years, enterprise data architectures have evolved significantly to accommodate the changing data requirements of modern businesses. Data warehouses were first introduced in the […] The post Are Data Warehouses Still Relevant?

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The MLOps Blog

MARCH 15, 2023

Automating myriad steps associated with pipeline data processing, helps you convert the data from its raw shape and format to a meaningful set of information that is used to drive business decisions. In this post, you will learn about the 10 best data pipeline tools, their pros, cons, and pricing.

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ODSC - Open Data Science

OCTOBER 15, 2023

Cloudera Cloudera is a cloud-based platform that provides businesses with the tools they need to manage and analyze data. They offer a variety of services, including data warehousing, data lakes, and machine learning. The platform includes several features that make it easy to develop and test data pipelines.

Machine Learning 52

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Pickl AI

JULY 25, 2024

Summary: Data ingestion is the process of collecting, importing, and processing data from diverse sources into a centralised system for analysis. This crucial step enhances data quality, enables real-time insights, and supports informed decision-making.

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Pickl AI

JULY 30, 2024

With a user-friendly interface and robust features, NiFi simplifies complex data workflows and enhances real-time data integration. Overview In the era of Big Data , organizations inundated with vast amounts of information generated from various sources.

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Precisely

SEPTEMBER 9, 2024

It’s important to note that end-to-end data observability of your complex data pipelines is a necessity if you’re planning to fully automate the monitoring, diagnosis, and remediation of data quality issues. Standardized processes for remediation of enterprise-wide data quality issues are beginning to gain traction.”

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Pickl AI

OCTOBER 17, 2024

Summary: The ETL process, which consists of data extraction, transformation, and loading, is vital for effective data management. Following best practices and using suitable tools enhances data integrity and quality, supporting informed decision-making. Introduction The ETL process is crucial in modern data management.

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ETL Data Warehouse SQL Data Quality 52

Tableau

DECEMBER 7, 2022

But good data—and actionable insights—are hard to get. Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments.

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Tableau

DECEMBER 7, 2022

But good data—and actionable insights—are hard to get. Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments.

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Tableau Data Warehouse Data Pipeline Data Visualization 98

Alation

JUNE 21, 2022

After that came data governance , privacy, and compliance staff. Power business users and other non-purely-analytic data citizens came after that. As the audience grew, so did the diversity of information assets they wanted in the catalog. Data scientists went beyond database tables to data lakes and cloud data stores.

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phData

AUGUST 20, 2024

For more information, see Adopt a Git Branching Strategy. This helps manage data drift and maintain the integrity of training and test sets. Data Lineage: Keeping a record of data transformations and preprocessing steps to ensure the data pipeline is reproducible and auditable. for more information.

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AWS Machine Learning Blog

JUNE 18, 2024

Through evaluations of sensors and informed decision-making support, Afri-SET empowers governments and civil society for effective air quality management. The attempt is disadvantaged by the current focus on data cleaning, diverting valuable skills away from building ML models for sensor calibration.

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IBM Journey to AI blog

SEPTEMBER 19, 2023

To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. By analyzing datasets, data scientists can better understand their potential use in an algorithm or machine learning model. Watsonx comprises of three powerful components: the watsonx.ai

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Dataconomy

FEBRUARY 23, 2023

They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. This involves working closely with data analysts and data scientists to ensure that data is stored, processed, and analyzed efficiently to derive insights that inform decision-making.

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Big Data Big Data Data Engineering Data Engineering 91

Alation

MARCH 22, 2022

They created each capability as modules, which can either be used independently or together to build automated data pipelines. The table details are extracted from the IDF pipeline information, which then syncs details like column, table, business, and technical metadata. How the IDF Supports a Smarter Data Pipeline.

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ODSC - Open Data Science

FEBRUARY 24, 2023

Data Quality Now that you’ve learned more about your data and cleaned it up, it’s time to ensure the quality of your data is up to par. With these data exploration tools, you can determine if your data is accurate, consistent, and reliable. You can watch it on demand here.

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phData

FEBRUARY 5, 2024

Walking you through the biggest challenges we have found when migrating our customer’s data from a legacy system to Snowflake. Background Information on Migrating to Snowflake So you’ve decided to move from your current data warehousing solution to Snowflake, and you want to know what challenges await you.

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IBM Journey to AI blog

DECEMBER 16, 2022

So, instead of wandering the aisles in hopes you’ll stumble across the book, you can walk straight to it and get the information you want much faster. An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more.

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Data Quality Data Governance Data Wrangling Data Scientist 52

Tableau

DECEMBER 7, 2022

But good data—and actionable insights—are hard to get. Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments.

Tableau 54

Tableau Data Warehouse Data Pipeline Data Visualization 54

IBM Journey to AI blog

OCTOBER 12, 2023

Securing AI models and their access to data While AI models need flexibility to access data across a hybrid infrastructure, they also need safeguarding from tampering (unintentional or otherwise) and, especially, protected access to data. But the implementation of AI is only one piece of the puzzle.

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AI AI Data Scientist Data Governance 101

Alation

APRIL 18, 2023

This, in turn, helps them to build new data pipelines, solutions, and products, or clean up the data that’s there. It bears mentioning data profiling has evolved tremendously. In the past, experts would need to write dozens of queries to extract this information over hours or days.

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The MLOps Blog

JUNE 27, 2023

Can you debug system information? Metadata management : Robust metadata management capabilities enable you to associate relevant information, such as dataset descriptions, annotations, preprocessing steps, and licensing details, with the datasets, facilitating better organization and understanding of the data.

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Flipboard

AUGUST 17, 2023

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. If you want to do the process in a low-code/no-code way, you can follow option C.

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IBM Journey to AI blog

JULY 17, 2023

These encoder-only architecture models are fast and effective for many enterprise NLP tasks, such as classifying customer feedback and extracting information from large documents. While they require task-specific labeled data for fine tuning, they also offer clients the best cost performance trade-off for non-generative use cases.

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IBM Journey to AI blog

OCTOBER 16, 2023

Most of today’s largest foundation models, including the large language model (LLM) powering ChatGPT, have been trained on information culled from the internet. But how trustworthy is that training data? It helps you streamline data engineering with reduced data pipelines, simplified data transformation and enriched data.

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phData

AUGUST 5, 2024

Data Clean Rooms also include privacy-enhanced techniques. For instance, differential privacy adds noise to query results as a means of preventing access to Personally Identifiable Information (PII) and running multi-party computations directly on encrypted data.

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IBM Journey to AI blog

JULY 1, 2024

Whenever anyone talks about data lineage and how to achieve it, the spotlight tends to shine on automation. This is expected, as automating the process of calculating and establishing lineage is crucial to understanding and maintaining a trustworthy system of data pipelines. Contact your IBM representative for more information.

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phData

DECEMBER 4, 2023

With the phData Provision Tool, you can: Quickly ramp up new projects through the reuse of information architecture Speed user onboarding and simplify access management Quickly apply new changes to Snowflake. For further information or assistance, phData recommends having deeper conversations with our technical experts.

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