Ascend.io

SEPTEMBER 14, 2023

High Performance Python is inherently efficient and robust, enabling data engineers to handle large datasets with ease: Speed & Reliability: At its core, Python is designed to handle large datasets swiftly , making it ideal for data-intensive tasks. show() So How Much Python Is Required for a Data Engineer?

Data Engineering 52

Data Engineering Data Engineer Python Engineering 52

Cloud Academy

JANUARY 27, 2022

A data engineer is an engineer who creates solutions from raw data. A data engineer develops, constructs, tests, and maintains data architectures. Let’s review some of the big picture concepts as well finer details about being a data engineer. Earlier we mentioned ETL or extract, transform, load.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

ProjectPro

JANUARY 19, 2022

Source: Image uploaded by Tawfik Borgi on (researchgate.net) So, what is the first step towards leveraging data? The first step is to work on cleaning it and eliminating the unwanted information in the dataset so that data analysts and data scientists can use it for analysis.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Knowledge Hut

NOVEMBER 28, 2023

Traditional data transformation tools are still relevant today, while next-generation Kafka, cloud-based tools, and SQL are on the rise for 2023. NoSQL If you think that Hadoop doesn't matter as you have moved to the cloud, you must think again. Data Engineer Soft Skills Data engineers are important members of big data teams.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

AltexSoft

AUGUST 29, 2023

The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. This article explains what a data lake is, its architecture, and diverse use cases. Raw data store section. Transformation section.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

ProjectPro

OCTOBER 15, 2014

Pig and Hive are the two key components of the Hadoop ecosystem. What does pig hadoop or hive hadoop solve? Pig hadoop and Hive hadoop have a similar goal- they are tools that ease the complexity of writing complex java MapReduce programs. Apache HIVE and Apache PIG components of the Hadoop ecosystem are briefed.

Hadoop 52

Hadoop Unstructured Data Java SQL 52

Knowledge Hut

JUNE 20, 2023

Factors Data Engineer Machine Learning Definition Data engineers create, maintain, and optimize data infrastructure for data. In addition, they are responsible for developing pipelines that turn raw data into formats that data consumers can use easily. Assess the needs and goals of the business.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

ProjectPro

FEBRUARY 16, 2023

According to the 8,786 data professionals participating in Stack Overflow's survey, SQL is the most commonly-used language in data science. Despite the buzz surrounding NoSQL , Hadoop , and other big data technologies, SQL remains the most dominant language for data operations among all tech companies.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

ProjectPro

DECEMBER 7, 2021

A pipeline may include filtering, normalizing, and data consolidation to provide desired data. It can also consist of simple or advanced processes like ETL (Extract, Transform and Load) or handle training datasets in machine learning applications. It can also be made accessible as an API and distributed to stakeholders.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Edureka

APRIL 17, 2023

What is the Role of Data Analytics? Data analytics is used to make sense of data and provide valuable insights to help organizations make better decisions. Data analytics aims to turn raw data into meaningful insights that can be used to solve complex problems.

Portfolio 40

Portfolio Data Analytics Project Data Mining 40

ProjectPro

JUNE 9, 2021

Data Science- Definition Data Science is an interdisciplinary branch encompassing data engineering and many other fields. Data Science involves applying statistical techniques to raw data, just like data analysts, with the additional goal of building business solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

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

Knowledge Hut

DECEMBER 26, 2023

If we look at history, the data that was generated earlier was primarily structured and small in its outlook. A simple usage of Business Intelligence (BI) would be enough to analyze such datasets. However, as we progressed, data became complicated, more unstructured, or, in most cases, semi-structured.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

ProjectPro

JULY 22, 2016

The desire to save every bit and byte of data for future use, to make data-driven decisions is the key to staying ahead in the competitive world of business operations. All this is possible due to the low cost storage systems like Hadoop and Amazon S3. The schema is defined only when the data is pulled and accessed for analysis.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

AltexSoft

JULY 29, 2022

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. The Hadoop toy. So the first secret to Hadoop’s success seems clear — it’s cute. What is Hadoop?

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

MAY 20, 2015

It provides the first purpose-built Adaptive Data Preparation Solution(launched in 2013) for data scientist, IT teams, data curators, developers, and business analysts -to integrate, cleanse and enrich raw data into meaningful analytic ready big data that can power operational, predictive , ad-hoc and packaged analytics.

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

Knowledge Hut

SEPTEMBER 6, 2023

To obtain a data science certification, candidates typically need to complete a series of courses or modules covering topics like programming, statistics, data manipulation, machine learning algorithms, and data analysis. You will learn about Python, SQL, statistical modeling and data analysis.

Data Science 97

Data Science Certification Business Analyst Machine Learning 97

U-Next

MARCH 7, 2023

Define Data Wrangling The process of data wrangling involves cleaning, structuring, and enriching raw data to make it more useful for decision-making. Data is discovered, structured, cleaned, enriched, validated, and analyzed. Values significantly out of a dataset’s mean are considered outliers.

Data Mining 96

Data Mining Scala Government Data Governance 96

Knowledge Hut

FEBRUARY 7, 2023

We will explore the basics of SAS in this article through an exploratory data analysis using the SAS environment.  DATA Step: The data step includes all SAS statements, beginning with line data and ending with line datalines. In this step, we can define and modify the values in the relevant dataset.

Data Science 52

Data Science Datasets SQL Data Mining 52

Edureka

JANUARY 18, 2024

Need for Data Science Data scientists play a vital part in improving decision-making, increasing business efficiency, and turning massive volumes of data into actionable insights. They manage intricate datasets, create forecasting models, and examine consumer behavior to deliver tailored experiences.

Data Science 40

Data Science Deep Learning NoSQL Machine Learning 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. Finally, the data is published and visualized on a Java-based custom Dashboard.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

JANUARY 31, 2023

Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data. Big data enables businesses to gain a deeper understanding of their industry and helps them extract valuable information from the unstructured and raw data that is regularly collected.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

AUGUST 11, 2021

Is Snowflake a data lake or data warehouse? Is Hadoop a data lake or data warehouse? Data Lake vs Data Warehouse - The Introduction What is a Data warehouse? According to Wikipedia , a Data Warehouse is defined as "a system used for reporting and data analysis.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Towards Data Science

DECEMBER 23, 2023

Reading and transforming data with PySpark : With our catch on board, we use PySpark, our compass, to navigate through this sea of data. PySpark helps us clean, organize, and make sense of our catch, transforming raw data into valuable insights, much like how a skilled chef would prepare a variety of dishes from the day’s catch.

SQL 75

SQL Data Analytics Hadoop Raw Data 75

ProjectPro

OCTOBER 27, 2021

Use the Pandas data frame to read and store your data. Also, remove all missing and NaN values from the dataset, as incomplete data is unnecessary. You can use the Huge Stock Market Dataset or the NY Stock Exchange Dataset to implement this machine learning project. Our data is imbalanced.

Finance 52

Finance Machine Learning Project Banking 52

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. No wonder only 0.5

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

MAY 14, 2021

As you now know the key characteristics, it gets clear that not all data can be referred to as Big Data. What is Big Data analytics? Big Data analytics is the process of finding patterns, trends, and relationships in massive datasets that can’t be discovered with traditional data management techniques and tools.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

JUNE 24, 2021

Data Cleaning: To improve the data quality and filter the noisy, inaccurate, and irrelevant data for analysis, data cleaning is a key skill needed for all analytics job roles. Microsoft Excel: A successful Excel spreadsheet helps to organize raw data into a more readable format.

Data Analytics 40

Data Analytics Project Insurance Hadoop 40

ProjectPro

DECEMBER 22, 2016

As data analysts salaries continue to rise with the entry-level data analyst earning an average of $50,000-$75,000 and experienced data analyst salary ranging from $65,000-$110,000, many IT professionals are embarking on a career as a Data analyst. Data analysis begins with a question or an assumption.

Data Mining 52

Data Mining Data Cleanse Datasets Data Analysis 52

ProjectPro

AUGUST 21, 2015

With the help of ProjectPro’s Hadoop Instructors, we have put together a detailed list of big data Hadoop interview questions based on the different components of the Hadoop Ecosystem such as MapReduce, Hive, HBase, Pig, YARN, Flume, Sqoop , HDFS, etc. What is the difference between Hadoop and Traditional RDBMS?

Hadoop 40

Hadoop Big Data Metadata Java 40

Knowledge Hut

JANUARY 18, 2024

Data Science initiatives from an operational standpoint help organizations optimize various aspects of their business, such as supply chain management , inventory segregation, and management, demand forecasting, etc. A data analyst would be a professional who will be able to accomplish all the tasks mentioned in the process of data analysis.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

ProjectPro

JULY 27, 2021

Data Engineer Interview Questions on Big Data Any organization that relies on data must perform big data engineering to stand out from the crowd. But data collection, storage, and large-scale data processing are only the first steps in the complex process of big data analysis.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

NOVEMBER 10, 2021

A data warehouse (DW) is a centralized repository for data accumulated from an array of corporate sources like CRMs, relational databases , flat files, etc. Typically used for data analysis and reporting, data warehouses rely on ETL mechanisms to extract , transform , and load data into a destination.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

U-Next

AUGUST 3, 2022

The Big Data age in the data domain has begun as businesses cope with petabyte and exabyte-sized amounts of data. Up until 2010, it was extremely difficult for companies to store data. Now that well-known technologies like Hadoop and others have resolved the storage issue, the emphasis is on information processing.

Retail 52

Retail Data Science Computer Science Entertainment 52

ProjectPro

APRIL 15, 2016

Preparing for a Hadoop job interview then this list of most commonly asked Apache Pig Interview questions and answers will help you ace your hadoop job interview in 2018. Research and thorough preparation can increase your probability of making it to the next step in any Hadoop job interview.

Hadoop 40

Hadoop Java Big Data SQL 40

ProjectPro

AUGUST 18, 2021

Making a career transition into data analysis and visualization? Ace your next data analyst interview with these Tableau interview questions and answers that cover all the important topics and concepts in Tableau. Translating the analyzed data to a visual context helps absorb new insights in a much better form.

BI 40

BI Database-centric SQL Software Engineer 40

AltexSoft

MAY 12, 2023

This article delves into the realm of unstructured data, highlighting its importance, and providing practical guidance on extracting valuable insights from this often-overlooked resource. We will discuss the different data types, storage and management options, and various techniques and tools for unstructured data analysis.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59