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

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

ProjectPro

JANUARY 31, 2022

As the demand for big data grows, an increasing number of businesses are turning to cloud data warehouses. The cloud is the only platform to handle today's colossal data volumes because of its flexibility and scalability. Launched in 2014, Snowflake is one of the most popular cloud data solutions on the market.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Data Engineering Weekly

MAY 5, 2024

The motivation for Machine Unlearning is critical from the privacy perspective and for model correction, fixing outdated knowledge, and access revocation of the training dataset. link] LinkedIn: LakeChime - A Data Trigger Service for Modern Data Lakes LinkedIn points out two critical flaws in a partitioned approach to data management.

Data Engineering 67

Data Engineering Data Engineer Engineering Google Cloud 67

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? However, it also severely limits the scope of the data.

Big Data 52

Big Data Relational Database Data Datasets 52

AltexSoft

MAY 14, 2021

Big Data enjoys the hype around it and for a reason. But the understanding of the essence of Big Data and ways to analyze it is still blurred. This post will draw a full picture of what Big Data analytics is and how it works. Also, we’ll introduce you to the popular Big Data analytics tools and existing use cases.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Data Engineering Weekly

APRIL 7, 2024

Poor data quality and unlcear data ownership remains the top challenges for the data teams. Data Mesh continuously gaining popularity among the enterprises. It is a stark difference from the Gartner report about data mesh. I guess only the time will tell who wins in the data mesh vs data fabric war.

Data Engineering 70

Data Engineering Data Engineer Engineering Unstructured Data 70

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

Monte Carlo

MAY 28, 2024

This involves connecting to multiple data sources, using extract, transform, load ( ETL ) processes to standardize the data, and using orchestration tools to manage the flow of data so that it’s continuously and reliably imported – and readily available for analysis and decision-making.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

Striim

MAY 1, 2024

UPS Capital recognizes the challenges faced by its customers in securing their package delivery ecosystem and is harnessing digital capabilities and data access to redefine traditional approaches, ensuring improved customer experiences and combating shipping loss.

Google Cloud 52

Google Cloud Insurance Finance Machine Learning 52

Towards Data Science

MAY 14, 2024

Dataform enables the application of software engineering best practices such as testing, environments, version control, dependencies management, orchestration and automated documentation to data pipelines. js for data transformations and logic. It is a serverless, SQL workflow orchestration workhorse within GCP. json config file.

Data Pipeline 71

Data Pipeline Coding Raw Data Accessible 71

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

Knowledge Hut

JUNE 28, 2023

This table highlights various aspects such as data mining for business intelligence concepts techniques and applications. It also entails data utilization, analysis techniques, user roles, and applications, allowing for a comprehensive comparison between business intelligence and data mining cycle.

Data Mining 52

Data Mining Business Intelligence BI Datasets 52

Knowledge Hut

MARCH 27, 2024

These are the situations where having a lot of data stored in one location and being able to access it quickly are necessary. What is a Data Structure? Using a data structure allows you to efficiently arrange data on a computer. Flexibility: Offers scalability to manage extensive datasets efficiently.

Database 52

Database Algorithm Relational Database PostgreSQL 52

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 Data Mining 97

Knowledge Hut

JANUARY 29, 2024

However, the sheer volume and complexity of raw data from various sources can often resemble a chaotic jigsaw puzzle. It is in this intricate process of assembling, cleaning, and refining data that the magic of Data Wrangling unfolds. Why Is Data Wrangling Important?

Raw Data 52

Raw Data Data Mining Data Preparation Structured Data 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

On the other hand, in non-linear data structures, the elements do not form a sequence. The choice between using a linear or non-linear data structure depends on the access patterns needed for the application. Also, we will learn about how to choose a data structure for a different use case, let's get started.

Algorithm 52

Algorithm Data Datasets Accessible 52

Knowledge Hut

JANUARY 19, 2024

Entering the world of data science is a strategic move in the 21st century, known for its lucrative opportunities. With businesses relying heavily on data, the demand for skilled data scientists has skyrocketed. Recognizing the growing need for data scientists, institutions worldwide are intensifying efforts to meet this demand.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

Knowledge Hut

DECEMBER 21, 2023

In this article, we will discuss the 10 most popular Hadoop tools which can ease the process of performing complex data transformations. It incorporates several analytical tools that help improve the data analytics process. With the help of these tools, analysts can discover new insights into the data. What is Hadoop?

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Monte Carlo

FEBRUARY 27, 2024

On one hand, everyone’s talking about whether GenAI’s not-insignificant data engineering skills are going to automate away their jobs. On the other, business leaders are realizing that slapping a quick ChatGPT integration into their product isn’t going to cut it — and they’re looking to data engineers for a better solution.

Data Engineering 59

Data Engineering Data Engineer Engineering High Quality Data 59

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 72

SQL Data Analytics Hadoop Raw Data 72

AltexSoft

JUNE 26, 2023

All successful companies do it: constantly collect data. While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. What is data collection?

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Monte Carlo

JUNE 6, 2023

Some teams view data quality mainly as a technical challenge while others look at it as a business or process problem. I have spoken to dozens of data leaders in the past year to understand how they approach data quality as part of their overall organizational goals. The whole needs to be greater than the sum of its parts.

Data Governance 98

Data Governance Government Data Data Engineering 98

Edureka

FEBRUARY 8, 2024

Whether you are hosting a website, running complex data analytics, or deploying machine learning models, the instance type serves as the foundation upon which your entire AWS architecture is built. In-Memory Caching- Memory-optimized instances are suitable for in-memory caching solutions, enhancing the speed of data access.

AWS 52

AWS NoSQL Deep Learning Datasets 52

AltexSoft

MAY 12, 2023

Of course, tapping into this immense pool of unstructured data may offer businesses a wealth of opportunities to better understand their customers, markets, and operations, ultimately driving growth and success. What is unstructured data? This mess of information is analogous to unstructured data. Social media posts.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Towards Data Science

MARCH 5, 2024

Introduction In the field of data warehousing, there’s a universal truth: managing data can be costly. But let me give you a magical spell to appease the dragon: burn data, not money! At its core, BigQuery is a serverless Data Warehouse for analytical purposes and built-in features like Machine Learning ( BigQuery ML ).

Bytes 69

Bytes Google Cloud Cloud Storage Utilities 69

Data Engineering Podcast

FEBRUARY 3, 2019

Introduction Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out Linode. What pieces of metadata do you track for a given data set?

Digital Media 100

Digital Media Media PostgreSQL Datasets 100

Rockset

MAY 21, 2024

Secondly, as LLMs are trained on datasets that are static and often outdated by the time they're deployed, they are unable to provide accurate or relevant information about recent developments or trends. How RAG Works RAG extends the capabilities of an LLM beyond its initial training data by providing more accurate and up-to-date responses.

Building 52

Building Utilities Datasets Database 52

Knowledge Hut

MAY 3, 2024

Perform iteration with enumerate() instead of range() Consider a situation during a coding interview: You have a list of elements, and you have to iterate over the list with the access to both the indices and values. How to Select the Correct Built-in Function? The built-in functions are always available and are not needed to be imported.

Python 98

Python Coding Data Programming 98

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 90

Data Analysis PostgreSQL Data Science SQL 90

Knowledge Hut

SEPTEMBER 26, 2023

The insights derived from the data in hand are then turned into impressive business intelligence visuals such as graphs or charts for the executive management to make strategic decisions. In this post, we will discuss the top power BI developer skills required to access Microsoft’s power business intelligence software.

BI 52

BI Business Intelligence Raw Data Data Analysis 52

AltexSoft

JUNE 7, 2021

They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Apache Hadoop is an open-source framework written in Java for distributed storage and processing of huge datasets. You don’t need to archive or clean data before loading.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Knowledge Hut

SEPTEMBER 26, 2023

Supports Structured and Unstructured Data: One of Azure Synapse's standout features is its versatility in handling a wide array of data types. Whether your data is structured, like traditional relational databases, or unstructured, such as textual data, images, or log files, Azure Synapse can manage it effectively.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Monte Carlo

JULY 13, 2023

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. Automation is a missing link in many organizations’ efforts toward data operationalization. Automating self-service access.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

Towards Data Science

JUNE 8, 2023

Some teams view data quality mainly as a technical challenge while others look at it as a business or process problem. I have spoken to dozens of data leaders in the past year to understand how they approach data quality as part of their overall organizational goals. The whole needs to be greater than the sum of its parts.

Data Governance 76

Data Governance Government Generalist Data Engineering 76

Knowledge Hut

MARCH 27, 2024

So long as they have access to a few brief notes, it becomes easy for students to review and go over the fundamental ideas and techniques. Because of its complete accessibility, user-friendliness, and strong community support, Python is the most popular programming language among aficionados for machine learning.

Machine Learning 52

Machine Learning Deep Learning Algorithm Certification 52