ODSC - Open Data Science

SEPTEMBER 27, 2023

They excel at managing structured data and supporting ACID (Atomicity, Consistency, Isolation, Durability) transactions. Scalability: Relational databases can scale vertically by upgrading hardware, but horizontal scaling can be more challenging due to the need to maintain data integrity and relationships.

Big Data 98

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IBM Journey to AI blog

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Perform data quality monitoring based on pre-configured rules.

Data Quality 130

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AWS Machine Learning Blog

MAY 15, 2023

Solution overview Six people from Getir’s data science team and infrastructure team worked together on this project. Deep/neural network algorithms also perform very well on sparse data set and in cold-start (new item introduction) scenarios. The following diagram shows the solution’s architecture.

Neural Network 93

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ODSC - Open Data Science

JUNE 7, 2023

Data lakes are able to handle a diverse range of data types. From images, videos, text, and even sensor data. Then, there’s data integration. A data lake can also act as a central hub for integrating data from various sources and systems within an organization.

Metadata 52

Metadata Data Science Machine Learning Python 52

AWS Machine Learning Blog

OCTOBER 2, 2024

However, scaling up generative AI and making adoption easier for different lines of businesses (LOBs) comes with challenges around making sure data privacy and security, legal, compliance, and operational complexities are governed on an organizational level. Tanvi Singhal is a Data Scientist within AWS Professional Services.

Generative AI 126

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ODSC - Open Data Science

FEBRUARY 21, 2024

These files contain metadata, current state details, and other information useful in planning and applying changes to infrastructure. It helps to observe data science principles in working with these files. They can provide encryption for passwords and other secrets to ensure state data integrity and confidentiality.

DevOps 52

DevOps Data Science Metadata Machine Learning 52

Pickl AI

JULY 19, 2024

They enhance data integrity, security, and accessibility while providing tools for efficient data management and retrieval. A Database Management System (DBMS) is specialised software designed to efficiently manage and organise data within a computer system. Indices are data structures optimised for rapid data retrieval.

Data Integration 52

Data Integration Metadata Big Data Business Intelligence 52

Pickl AI

JUNE 11, 2024

These are subject-specific subsets of the data warehouse, catering to the specific needs of departments like marketing or sales. They offer a focused selection of data, allowing for faster analysis tailored to departmental goals. Metadata This acts like the data dictionary, providing crucial information about the data itself.

ETL 52

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Flipboard

NOVEMBER 24, 2023

Iris was designed to use machine learning (ML) algorithms to predict the next steps in building a data pipeline. By analyzing millions of metadata elements and data flows, Iris could make intelligent suggestions to users, democratizing data integration and allowing even those without a deep technical background to create complex workflows.

ETL 153

ETL Prompt Engineer Prompt Engineering Generative AI 153

Pickl AI

NOVEMBER 15, 2023

From financial services to e-commerce and telecommunications, organizations leverage Data Warehouses to unlock the full potential of their structured data for strategic advantage. What Is Data Lake Architecture? Delta Lake vs. Data Lake Delta Lake is an open-source storage layer that brings ACID transactions to Data Lakes.

ETL 52

ETL Business Intelligence Metadata Data Analysis 52

Pickl AI

AUGUST 31, 2023

Types of Data Profiling: Data profiling can be broadly categorized into three main types, each focusing on different aspects of the data: Structural Profiling: Structural profiling involves analyzing the structure and metadata of the data. It supports metadata analysis, data lineage, and data quality assessment.

ETL 52

ETL Data Quality Data Integration Metadata 52

Pickl AI

OCTOBER 11, 2023

This process involves real-time monitoring and documentation to provide visibility on the data quality, thereby helping the organization detect and address data-related issues. It is backed by sophisticated algorithms that empower the identification of budding data irregularities Simplify the amalgamation of data from diverse origins.

Data Quality 52

Data Quality Metadata Automation Data Science 52

Pickl AI

OCTOBER 11, 2024

These include the database engine for executing queries, the query processor for interpreting SQL commands, the storage manager for handling physical data storage, and the transaction manager for ensuring data integrity through ACID properties. Data Independence: Changes in database structure do not affect application programs.

Data Integration 52

Data Integration Metadata Big Data Algorithm 52

Pickl AI

JUNE 28, 2023

With the use of these tools, one can streamline the data modelling process. Moreover, these tools are designed to automate tasks like generating SQL scripts, documenting metadata and others. Improved Visualization Data modelling tools offer intuitive graphical representations of data models.

Metadata 52

Metadata Data Integration Automation Software Development 52

Pickl AI

JANUARY 22, 2025

Introduction In today’s data-driven world, organizations generate approximately 2.5 quintillion bytes of data daily, highlighting the critical need for efficient data management. Database Management Systems (DBMS) serve as the backbone of data handling.

Data Integration 52

Data Integration ETL Metadata Data Extraction 52

Pickl AI

OCTOBER 21, 2024

The primary purpose of a DBMS is to provide a systematic way to manage large amounts of data, ensuring that it is organised, accessible, and secure. By employing a DBMS, organisations can maintain data integrity, reduce redundancy, and streamline data operations, enabling more informed decision-making.

Data Integration 52

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Pickl AI

JULY 23, 2023

It requires sophisticated tools and algorithms to derive meaningful patterns and trends from the sheer magnitude of data. Meta Data Metadata, often dubbed “data about data,” provides essential context and descriptions for other datasets. To know more about Pickl.AI

Data Analysis 52

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Pickl AI

OCTOBER 10, 2023

Data Transparency Data Transparency is the pillar that ensures data is accessible and understandable to all stakeholders within an organization. This involves creating data dictionaries, documentation, and metadata. It provides clear insights into the data’s structure, meaning, and usage.

Data Quality 52

Data Quality Machine Learning Data Science Data Integration 52

Pickl AI

MAY 15, 2023

Online Processing: this type of data processing involves managing transactional data in real time and focuses on handling individual transaction. The systems are designed to ensure data integrity, concurrency and quick response times for enabling interactive user transactions. The Data Science courses provided by Pickl.AI

Machine Learning 52

Machine Learning Data Analysis Data Integration Metadata 52

Pickl AI

OCTOBER 19, 2023

This includes removing duplicates, correcting typos, and standardizing data formats. It forms the bedrock of data quality improvement. Implement Data Validation Rules To maintain data integrity, establish strict validation rules. This ensures that the data entered meets predefined criteria.

Data Quality 52

Data Quality ETL Machine Learning Data Ingestion 52

Artificial Corner

JUNE 6, 2023

The benefits of Databricks over Spark is Highly reliable and performant data pipelines and Productive data science at scale — source: [link] Databricks also introduced Delta Lake, an open-source storage layer that brings reliability to data lakes. MapReduce: simplified data processing on large clusters.

Data Mining 52

Data Mining Big Data ETL Machine Learning 52

The MLOps Blog

OCTOBER 3, 2023

So I was able to get from growth hacking to data analytics, then data analytics to data science, and then data science to MLOps. I switched from analytics to data science, then to machine learning, then to data engineering, then to MLOps. How do I get this model in production?

ML 52

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