Knowledge Hut

APRIL 23, 2024

Big data has revolutionized the world of data science altogether. With the help of big data analytics, we can gain insights from large datasets and reveal previously concealed patterns, trends, and correlations. Learn more about the 4 Vs of big data with examples by going for the Big Data certification online course.

Big Data 52

Big Data Media Datasets Unstructured Data 52

Knowledge Hut

DECEMBER 21, 2023

In the present-day world, almost all industries are generating humongous amounts of data, which are highly crucial for the future decisions that an organization has to make. This massive amount of data is referred to as “big data,” which comprises large amounts of data, including structured and unstructured data that has to be processed.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Knowledge Hut

APRIL 23, 2024

In the modern data-driven landscape, organizations continuously explore avenues to derive meaningful insights from the immense volume of information available. Two popular approaches that have emerged in recent years are data warehouse and big data. Big data offers several advantages.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Data Engineering Weekly

SEPTEMBER 18, 2024

Decoupling of Storage and Compute : Data lakes allow observability tools to run alongside core data pipelines without competing for resources by separating storage from compute resources. This opens up new possibilities for monitoring and diagnosing data issues across various sources.

Data Lake 98

Data Lake Data Pipeline Unstructured Data Datasets 98

Monte Carlo

JANUARY 5, 2024

Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. The data lakehouse’s semantic layer also helps to simplify and open data access in an organization.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. The data lakehouse’s semantic layer also helps to simplify and open data access in an organization.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

NOVEMBER 9, 2023

In my opinion, enterprise ready generative AI must be: Secure & private: Your AI application must ensure that your data is secure, private, and compliant, with proper access controls. We *know* what we’re putting in (raw, often unstructured data) and we *know* what we’re getting out, but we don’t know how it got there.

Unstructured Data 86

Unstructured Data Database Data Pipeline Architecture 86

Data Engineering Weekly

APRIL 7, 2024

[link] Matt Turck: Full Steam Ahead: The 2024 MAD (Machine Learning, AI & Data) Landscape Coninue the week of insights into the world of data & AI landscape, the 2024 MAD landscape is out. We index only top-tier tables, promoting the use of these higher-quality datasets.

Data Engineering 70

Data Engineering Data Engineer Engineering Unstructured Data 70

AltexSoft

JUNE 26, 2023

We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection? It’s the first and essential stage of data-related activities and projects, including business intelligence , machine learning , and big data analytics.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

MAY 23, 2024

Data science professionals are scattered across various industries. This data science tool helps in digital marketing & the web admin can easily access, visualize, and analyze the website traffic, data, etc., A lot of MNCs and Fortune 500 companies are utilizing this tool for statistical modeling and data analysis.

Data Science 52

Data Science MongoDB Programming Language Hadoop 52

Striim

OCTOBER 11, 2024

Data pipelines are significant to businesses because they: Consolidate Data: Data pipelines are responsible for integrating and unifying data from diverse sources and formats, making it consistent and usable for analytics and business intelligence.

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 52

Knowledge Hut

JULY 28, 2023

Data Types and Dimensionality ML algorithms work well with structured and tabular data, where the number of features is relatively small. DL models excel at handling unstructured data such as images, audio, and text, where the data has a large number of features or high dimensionality.

Deep Learning 52

Deep Learning Machine Learning Unstructured Data Algorithm 52

Cloudera

DECEMBER 19, 2023

Limit access and capabilities initially. Improve dataset quality. Ensure you can trust your data by using only diverse, high-quality training data that represents different demographics and viewpoints. Our government leaders had several suggestions: Start small. Start with narrow, low-risk use cases.

Government 89

Government Education Unstructured Data Algorithm 89

Knowledge Hut

DECEMBER 26, 2023

In the twenty-first century, data science is regarded as a profitable career. It is simply the study of mathematics, statistics, and computer science to extract information from structured and unstructured data. Data science, which solves problems by connecting relevant data for later use, aids these emerging technologies.

Data Science 52

Data Science Unstructured Data Medical Healthcare 52

Edureka

JUNE 7, 2024

paintings, songs, code) Historical data relevant to the prediction task (e.g., Generative AI leverages the power of deep learning to build complex statistical models that process and mimic the structures present in different types of data.

Deep Learning 114

Deep Learning Media Manufacturing Algorithm 114

Striim

SEPTEMBER 11, 2024

Understanding the essential components of data pipelines is crucial for designing efficient and effective data architectures. Data warehouses offer high performance and scalability, enabling organizations to manage large volumes of structured data efficiently.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Monte Carlo

FEBRUARY 15, 2023

Data can be loaded using a loading wizard, cloud storage like S3, programmatically via REST API, third-party integrators like Hevo, Fivetran, etc. Data can be loaded in batches or can be streamed in near real-time. Structured, semi-structured, and unstructured data can be loaded.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Monte Carlo

JANUARY 23, 2024

Gen AI can whip up serviceable code in moments — making it much faster to build and test data pipelines. Today’s LLMs can already process enormous amounts of unstructured data, automating much of the monotonous work of data science. But what does that mean for the roles of data engineers and data scientists going forward?

Pipeline-centric 52

Pipeline-centric Database-centric Metadata Unstructured Data 52

Towards Data Science

DECEMBER 4, 2023

We’ll build a data architecture to support our racing team starting from the three canonical layers : Data Lake, Data Warehouse, and Data Mart. Data Lake A data lake would serve as a repository for raw and unstructured data generated from various sources within the Formula 1 ecosystem: telemetry data from the cars (e.g.

Data Engineering 82

Data Engineering Data Engineer Engineering Data Lake 82

Monte Carlo

APRIL 24, 2023

Amazon S3 and/or Lake Formation Amazon S3 is a popular storage platform to build and store data lakes thanks to its high availability and low latency access. S3 has seamless integration with the AWS ecosystem including AWS Glue for data cataloging, Amazon Athena for ad-hoc querying, and Amazon Redshift for data warehousing.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

ProjectPro

FEBRUARY 8, 2023

Scale Existing Python Code with Ray Python is popular among data scientists and developers because it is user-friendly and offers extensive built-in data processing libraries. For analyzing huge datasets, they want to employ familiar Python primitive types. Glue works absolutely fine with structured as well as unstructured data.

AWS 98

AWS Scala Metadata Data Lake 98

Knowledge Hut

APRIL 23, 2024

Below are some of the differences between Traditional Databases vs big data: Parameters Big Data Traditional Data Flexibility Big data is more flexible and can include both structured and unstructured data. Traditional Data is based on a static schema that can only work well with structured data.

Big Data 52

Big Data Relational Database Data Datasets 52

Knowledge Hut

JUNE 26, 2023

When screening resumes, most hiring managers prioritize candidates who have actual experience working on data engineering projects. Top Data Engineering Projects with Source Code Data engineers make unprocessed data accessible and functional for other data professionals. Which queries do you have?

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Knowledge Hut

DECEMBER 22, 2023

Linear Algebra Linear Algebra is a mathematical subject that is very useful in data science and machine learning. A dataset is frequently represented as a matrix. Statistics Statistics are at the heart of complex machine learning algorithms in data science, identifying and converting data patterns into actionable evidence.

Hadoop 98

Hadoop Deep Learning Data Science Machine Learning 98

Monte Carlo

MAY 14, 2024

Depending on the quantity of data flowing through an organization’s pipeline — or the format the data typically takes — the right modern table format can help to make workflows more efficient, increase access, extend functionality, and even offer new opportunities to activate your unstructured data.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Knowledge Hut

JANUARY 30, 2024

In summary, data extraction is a fundamental step in data-driven decision-making and analytics, enabling the exploration and utilization of valuable insights within an organization's data ecosystem. What is the purpose of extracting data? The process of discovering patterns, trends, and insights within large datasets.

ETL Tools 52

ETL Tools Database-centric Data Mining Raw Data 52

ProjectPro

JANUARY 31, 2023

Big data enables businesses to get valuable insights into their products or services. Almost every company employs data models and big data technologies to improve its techniques and marketing campaigns. Most leading companies use big data analytical tools to enhance business decisions and increase revenues.

Big Data 52

Big Data Hadoop Relational Database AWS 52

Cloudera

SEPTEMBER 9, 2022

Imagine having self-service access to all business data, anywhere it may be, and being able to explore it all at once. Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested. An architectural innovation: Cloudera Data Platform (CDP) and Apache Iceberg.

Architecture 101

Architecture Metadata Machine Learning Unstructured Data 101

Knowledge Hut

NOVEMBER 2, 2023

Professionals deploy databases, manage credentials and access, and integrate with other AWS services or applications. Implementing Basic IAM Security Difficulty Level: Beginner AWS cloud practitioner projects permit the implementation of Identity and Access Management (IAM) fundamental security controls.

AWS 52

AWS Coding Cloud Project 52

Cloudera

DECEMBER 11, 2020

As mentioned in my previous blog on the topic , the recent shift to remote working has seen an increase in conversations around how data is managed. Toolsets and strategies have had to shift to ensure controlled access to data. It established a data governance framework within its enterprise data lake.

Data Lake 98

Data Lake Government Data Security Unstructured Data 98

Knowledge Hut

DECEMBER 26, 2023

According to the Cybercrime Magazine, the global data storage is projected to be 200+ zettabytes (1 zettabyte = 10 12 gigabytes) by 2025, including the data stored on the cloud, personal devices, and public and private IT infrastructures. The dataset can be either structured or unstructured or both.

Data Science 97

Data Science BI Business Intelligence Machine Learning 97

Knowledge Hut

DECEMBER 22, 2023

Power BI Desktop Power BI Desktop is free software that can be downloaded and installed to build reports by accessing data easily without the need for advanced report designing or query skills to build a report. Multiple Data Sources Multiple Data Sources support various data sources like Excel, CSV, SQL Server, Web files, etc.

BI 98

BI Business Intelligence Machine Learning SQL 98

U-Next

AUGUST 25, 2022

A distributed systems architecture allows you to intelligently place data wherever you want it. A fully accessible documentation store called MongoDB allows us to interact with data extremely effectively while storing a lot of it. Due to its NoSQL database, the data is kept as a collection and documents. What is MongoDB?

MongoDB 40

MongoDB Architecture NoSQL MySQL 40

AltexSoft

AUGUST 29, 2023

Unstructured data sources. This category includes a diverse range of data types that do not have a predefined structure. Examples of unstructured data can range from sensor data in the industrial Internet of Things (IoT) applications, videos and audio streams, images, and social media content like tweets or Facebook posts.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

APRIL 23, 2024

Big Data certification course will support you in learning big data skills from the greatest mentors to help you build a career in big data. Top 10 Disadvantages of Big Data 1. Need for Skilled Personnel We see data in different forms; it can be categorized into structured, semi-structured, and unstructured data.

Big Data 52

Big Data Media Government Big Data Skills 52

AltexSoft

MAY 27, 2022

The tool processes both structured and unstructured data associated with patients to evaluate the likelihood of their leaving for a home within 24 hours. The main sources of such data are electronic health record ( EHR ) systems which capture tons of important details. Inpatient data anonymization. Factors impacting LOS.

Hospitality 98

Hospitality Medical Healthcare Algorithm 98

Data Engineering Weekly

MARCH 3, 2024

This approach led to a successful expansion of Copilot access across the engineering team, resulting in a significant increase in productivity and adoption, demonstrating a commitment to enhancing developer experience while maintaining safety and security standards. link] Nvidia: What Is Sovereign AI?

Data Engineering 67

Data Engineering Data Engineer Pipeline-centric Engineering 67