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. Data warehousing offers several advantages.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Snowflake

NOVEMBER 2, 2023

Over the years, the technology landscape for data management has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. These patterns include both centralized storage patterns like data warehouse , data lake and data lakehouse , and distributed patterns such as data mesh.

Data Lake 90

Data Lake Data Warehouse Cloud Unstructured Data 90

Monte Carlo

MAY 28, 2024

A data ingestion architecture is the technical blueprint that ensures that every pulse of your organization’s data ecosystem brings critical information to where it’s needed most. Ensuring all relevant data inputs are accounted for is crucial for a comprehensive ingestion process.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

Snowflake

MARCH 14, 2024

As a cohesive ERP solution, SAP is often one of the largest data resources in an organization, containing everything from financial and transactional data to master information about customers, vendors, materials, facilities, planning and even HR. What’s the challenge with unlocking SAP data?

IT 91

IT Data Ingestion Data AWS 91

Knowledge Hut

APRIL 23, 2024

Data storing and processing is nothing new; organizations have been doing it for a few decades to reap valuable insights. Compared to that, Big Data is a much more recently derived term. So, what exactly is the difference between Traditional Data and Big Data? Traditional Data uses centralized architecture.

Big Data 52

Big Data Relational Database Data Datasets 52

Snowflake

JUNE 4, 2024

Generative AI presents enterprises with the opportunity to extract insights at scale from unstructured data sources, like documents, customer reviews and images. It also presents an opportunity to reimagine every customer and employee interaction with data to be done via conversational applications.

Data Security 94

Data Security Machine Learning Unstructured Data SQL 94

ProjectPro

JANUARY 25, 2022

Did you know that, according to Linkedin, over 24,000 Big Data jobs in the US list Apache Spark as a required skill? Learning Spark has become more of a necessity to enter the Big Data industry. Python is one of the most extensively used programming languages for Data Analysis, Machine Learning , and data science tasks.

Big Data 52

Big Data Data Process Process Kafka 52

Snowflake

JANUARY 24, 2024

Governments collect more data than any other type of entity on the planet, yet their ability to use data to serve citizens more effectively has always been limited. For their full insights, read the new report, Public Sector Data + AI Predictions 2024.

Government 97

Government Data Management Cloud Data 97

Knowledge Hut

FEBRUARY 29, 2024

Being a data scientist means constantly growing, enabling businesses to become more data-propelled, and learning newer trends and tools. There are various excellent resources in data science that can help you to develop your skillset. So, having the right knowledge of tools and technology is important for handling such data.

Data Science 98

Data Science Datasets Database Design Machine Learning 98

Knowledge Hut

MARCH 20, 2024

Data is the primary focus of computer programming. The flow of data is what makes an application or project functional, and it is over this data that all business logic is built. For optimal utilization, it is therefore essential to arrange and store the data and use a solid data model for efficient programming.

Computer Science 52

Computer Science Programming Language Algorithm Software Engineer 52

Snowflake

MARCH 18, 2024

This time it’s all about ensuring that the data and the platform where it’s processed are ready for the new AI models. But there’s still a long way to go in an environment where the volume, velocity and complexity of data and data types is constantly increasing. And it’s not just any type of data.

Unstructured Data 86

Unstructured Data Government Data Pipeline Cloud 86

Knowledge Hut

JANUARY 29, 2024

In today's data-driven world, where information reigns supreme, businesses rely on data to guide their decisions and strategies. However, the sheer volume and complexity of raw data from various sources can often resemble a chaotic jigsaw puzzle. What Is Data Wrangling? Why Is Data Wrangling Important?

Raw Data 52

Raw Data Data Mining Data Preparation Structured Data 52

Knowledge Hut

JANUARY 30, 2024

In today's world, where data rules the roost, data extraction is the key to unlocking its hidden treasures. As someone deeply immersed in the world of data science, I know that raw data is the lifeblood of innovation, decision-making, and business progress. What is data extraction?

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

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

Monte Carlo

AUGUST 25, 2023

Modern companies are ingesting, storing, transforming, and leveraging more data to drive more decision-making than ever before. Data teams need to balance the need for robust, powerful data platforms with increasing scrutiny on costs. But, the options for data storage are evolving quickly. Let’s dive in.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

U-Next

MARCH 1, 2023

Introduction Data Engineer is responsible for managing the flow of data to be used to make better business decisions. A solid understanding of relational databases and SQL language is a must-have skill, as an ability to manipulate large amounts of data effectively. In 2022, data engineering will hold a share of 29.8%

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

Snowflake

MARCH 30, 2023

A 2016 data science report from data enrichment platform CrowdFlower found that data scientists spend around 80% of their time in data preparation (collecting, cleaning, and organizing of data) before they can even begin to build machine learning (ML) models to deliver business value.

Engineering 83

Engineering Raw Data Data Science Scala 83

Knowledge Hut

DECEMBER 26, 2023

According to the World Economic Forum, the amount of data generated per day will reach 463 exabytes (1 exabyte = 10 9 gigabytes) globally by the year 2025. Thus, almost every organization has access to large volumes of rich data and needs “experts” who can generate insights from this rich data.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

Towards Data Science

DECEMBER 23, 2023

Photo by Ian Taylor on Unsplash This tutorial guides you through an analytics use case, analyzing semi-structured data with Spark SQL. We’ll start with the data engineering process, pulling data from an API and finally loading the transformed data into a data lake (represented by MinIO ).

SQL 69

SQL Data Analytics Hadoop Raw Data 69

Monte Carlo

JUNE 6, 2023

Sure, data quality is everyones’ problem. But who is responsible for data quality? Some organizations will attempt to diffuse the responsibility widely across data stewards, data owners, data engineering and governance committees, each owning a fraction of the data value chain.

Data Governance 98

Data Governance Government Data Data Engineering 98

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

Ascend.io

FEBRUARY 28, 2024

The rise of generative AI is changing more than just technology; it’s reshaping our professional landscapes — and yes, data engineering is directly experiencing the impact. How does AI recalibrate the workload and priorities of data teams? How can data engineers harness the power of AI?

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Knowledge Hut

MARCH 22, 2024

Data structures are classified as linear or non-linear based on how they organise data in memory. The difference between linear and nonlinear data structures lies in their organisation and handling of data, with linear structures offering simplicity and sequence, while non-linear structures provide complexity and connectivity.

Algorithm 52

Algorithm Data Datasets Accessible 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Data Lake Management Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Management Data Lake Data Warehouse 52

Knowledge Hut

JUNE 28, 2023

In our data-driven world, our lives are governed by big data. The TV shows we watch, the social media we follow, the news we read, and even the optimized routes we take to work are all influenced by the power of big data analytics. The answer lies in the strategic utilization of business intelligence for data mining (BI).

Data Mining 52

Data Mining Business Intelligence BI Datasets 52

Knowledge Hut

APRIL 25, 2024

One of the industries with the quickest growth rates is big data. It refers to gathering and processing sizable amounts of data to produce insights that may be used by an organization to improve its various facets. You must become familiar with the fundamental elements of big data to comprehend it effectively.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

Knowledge Hut

MARCH 28, 2024

Have you ever wondered how large amounts of data are organized and accessed by computers? This magic lies in the world of data structures. Learning data structures is like understanding computer language. This will give you an idea of how the programs are processed effectively.

Algorithm 52

Algorithm Java Utilities Data 52

Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. In this article, we’ll focus on a data lake vs. data warehouse.

Data Lake 59

Data Lake Data Warehouse Hadoop Raw Data 59

Knowledge Hut

MAY 3, 2024

Let us look into some of the built-in functions provided by Python and how to select the correct one, learn about the effective use of data structures, how standard libraries in Python can be utilized and so on. Go through our best advanced python course to learn more about concepts related to Python.

Python 98

Python Coding Data Programming 98

Monte Carlo

JULY 13, 2023

Data-driven organizations generate, collect, and store vast amounts of data. To effectively manage and analyze this data, data engineering teams must navigate a wide range of challenges, including data access, security, compliance, and data observability. Automating self-service access.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

Cloudera

JUNE 3, 2022

Data scientists and machine learning engineers in enterprise organizations need to fully understand their data in order to properly analyze it, build models, and power machine learning use cases across their business. Data scientists are likely to use a variety of different tools to move through their processes.

Data Analysis 92

Data Analysis PostgreSQL Data Science SQL 92

Edureka

JUNE 7, 2024

Industry Applications of Predictive AI While both involve machine learning and data analysis, they differ in their core objectives and approaches. paintings, songs, code) Historical data relevant to the prediction task (e.g., paintings, songs, code) Historical data relevant to the prediction task (e.g.,

Deep Learning 114

Deep Learning Media Manufacturing Algorithm 114

Knowledge Hut

MARCH 27, 2024

Data tracking is becoming more and more important as technology evolves. A global data explosion is generating almost 2.5 quintillion bytes of data today, and unless that data is organized properly, it is useless. What Is Big Data Analytics? Some important big data processing platforms are: Microsoft Azure.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52