Precisely

MARCH 9, 2023

Data warehouse vs. data lake, each has their own unique advantages and disadvantages; it’s helpful to understand their similarities and differences. In this article, we’ll focus on a data lake vs. data warehouse. They may want to look at those numbers on a daily or weekly basis.

Data Lake 57

Data Lake Data Warehouse Hadoop Raw Data 57

Ascend.io

NOVEMBER 21, 2023

Yet, looking into the complexities of today’s data-driven world, it becomes clear that ELT, while transformative at its inception, now forms just a part of an ever-evolving data landscape. This article revisits the foundational elements of ELT, exploring what it is, how it reshaped data strategies, and how it works.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Knowledge Hut

APRIL 25, 2024

You'll be better able to comprehend the complex ideas in this field if you have a solid understanding of the characteristics of big data in data analytics and a list of essential features for new data platforms. What Are the Different Features of Big Data Analytics?

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

Monte Carlo

FEBRUARY 15, 2023

Data analysts and engineers can run the queries they want to run when they want to run them without worrying about excessive load times or statement timeouts. Cleaning Bad data can derail an entire company, and the foundation of bad data is unclean data. Data Security Data Warehouses achieve security in multiple ways.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Grouparoo

JANUARY 11, 2022

When it comes to storing large volumes of data, a simple database will be impractical due to the processing and throughput inefficiencies that emerge when managing and accessing big data. This article looks at the options available for storing and processing big data, which is too large for conventional databases to handle.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

AltexSoft

MARCH 14, 2023

This development has paved the way for a suite of cloud-native data tools that are user-friendly, scalable, and affordable. Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. Data democratization.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Ascend.io

AUGUST 31, 2023

Secondly , the rise of data lakes that catalyzed the transition from ELT to ELT and paved the way for niche paradigms such as Reverse ETL and Zero-ETL. Still, these methods have been overshadowed by EtLT — the predominant approach reshaping today’s data landscape.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Knowledge Hut

DECEMBER 26, 2023

What is Data Science? What are the roles and responsibilities of a Data Engineer? How does one become a Data engineer, and what skills are required? Our primary focus in this article will be to answer all these questions and take you a step forward towards your dream of becoming a Data engineer. And many more.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

AltexSoft

MARCH 30, 2023

Along with thousands of other data-driven organizations from different industries, the above-mentioned leaders opted for Databrick to guide strategic business decisions. In this article, we’ll highlight the reasoning behind this choice and the challenges related to it.

Scala 64

Scala Data Lake BI Google Cloud 64

Knowledge Hut

MARCH 27, 2024

The collection of meaningful market data has become a critical component of maintaining consistency in businesses today. A company can make the right decision by organizing a massive amount of raw data with the right data analytic tool and a professional data analyst. What Is Big Data Analytics?

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

Knowledge Hut

JULY 28, 2023

Below is a thorough article on Machine Learning vs Deep Learning. DL models automatically learn features from raw data, eliminating the need for explicit feature engineering. Prediction/Inference : Applying the trained model to make predictions or classifications on new, unseen data.

Deep Learning 52

Deep Learning Machine Learning Unstructured Data Algorithm 52

AltexSoft

NOVEMBER 10, 2021

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Traditional data warehouse platform architecture. Another type of data storage — a data lake — tried to address these and other issues.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Knowledge Hut

JANUARY 18, 2024

4 Purpose Utilize the derived findings and insights to make informed decisions The purpose of AI is to provide software capable enough to reason on the input provided and explain the output 5 Types of Data Different types of data can be used as input for the Data Science lifecycle.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

Monte Carlo

AUGUST 31, 2023

Data is a priority for your CEO, as it often is for digital-first companies, and she is fluent in the latest and greatest business intelligence tools. Your CTO is excited about migrating to the cloud, and constantly sends your team articles highlighting performance measurements against some of the latest technologies.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Monte Carlo

APRIL 1, 2021

Over the past few years, data lakes have emerged as a must-have for the modern data stack. But while the technologies powering our access and analysis of data have matured, the mechanics behind understanding this data in a distributed environment have lagged behind. Who has access to it?

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

U-Next

OCTOBER 25, 2022

What Is Data Manipulation? . In data manipulation, data is organized in a way that makes it easier to read, or that makes it more visually appealing, or that makes it more structured. Data collections can be organized alphabetically to make them easier to understand. . within an organization. .

Business Intelligence 40

Business Intelligence Raw Data Data Cleanse Data Analysis 40

Monte Carlo

JUNE 14, 2023

This frequently involves, in some order, extraction (from a source system), transformation (where data is combined with other data and put into the desired format), and loading (into storage where it can be accessed). Most organizations deploy some or all of these data pipeline architectures.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

U-Next

OCTOBER 20, 2022

Secondary Data Collection Methods . Secondary data refers to information collected by someone other than the researcher. Public data is easily accessible and does not require specialized data collection techniques. What Are Data Collection Tools? . Challenges in Maintaining Data Integrity .

Data Collection 52

Data Collection Big Data Data Medical 52

AltexSoft

JULY 29, 2022

What does it take to store all New York Times articles published between 1855 and 1922? Depending on how you measure it, the answer will be 11 million newspaper pages or… just one Hadoop cluster and one tech specialist who can move 4 terabytes of textual data to a new location in 24 hours. How HDFS master-slave structure works.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

AltexSoft

SEPTEMBER 23, 2021

Evidently, common storage solutions fail to provide a unified data view and meet the needs of companies for seamless data flow. One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. Data access layer: data querying.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

AltexSoft

SEPTEMBER 10, 2021

Information often resides across countless distributed data sources, resulting in data silos. To get a single unified view of all information, companies opt for data integration. What is data integration and why is it important? A newer way to integrate data into a centralized location is ELT. Data replication.

Data Integration 52

Data Integration Data Consolidation Data Warehouse BI 52

ProjectPro

MAY 31, 2021

To build a big data project, you should always adhere to a clearly defined workflow. Before starting any big data project, it is essential to become familiar with the fundamental processes and steps involved, from gathering raw data to creating a machine learning model to its effective implementation.

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

JULY 22, 2016

There are several people writing that data lakes are replacing data warehouses but this is just another technology hype that is coming across the effective use of data. Will data lake replace a data warehouse or will the two complement each other is currently the hottest discussion in the big data community.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

ProjectPro

AUGUST 24, 2021

Within no time, most of them are either data scientists already or have set a clear goal to become one. Nevertheless, that is not the only job in the data world. And, out of these professions, this blog will discuss the data engineering job role. Google BigQuery receives the structured data from workers.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

NOVEMBER 14, 2015

Hadoop Common houses the common utilities that support other modules, Hadoop Distributed File System (HDFS™) provides high throughput access to application data, Hadoop YARN is a job scheduling framework that is responsible for cluster resource management and Hadoop MapReduce facilitates parallel processing of large data sets.

Hadoop 52

Hadoop Project Big Data Healthcare 52