Knowledge Hut

JUNE 15, 2023

Every business unit, including marketing , production, and finance, uses data to make significant decisions and carry out its operations. That is why every organization works towards designing and building structures for proper data storage and analysis. This process of data management is called data engineering.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52

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. Of course, handling such huge amounts of data and using them to extract data-driven insights for any business is not an easy task; and this is where Data Science comes into the picture.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

Knowledge Hut

NOVEMBER 28, 2023

As a Data Engineer, you must: Work with the uninterrupted flow of data between your server and your application. Work closely with software engineers and data scientists. Data Visualization To successfully fulfill ETL or ELT-related work, you must be well-versed in exploratory data analysis (EDA).

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Knowledge Hut

JUNE 26, 2023

If you want to break into the field of data engineering but don't yet have any expertise in the field, compiling a portfolio of data engineering projects may help. Data pipeline best practices should be shown in these initiatives. However, the abundance of data opens numerous possibilities for research and analysis.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Knowledge Hut

JUNE 20, 2023

In this section, we will explore how database technology is being used to analyze spatio-temporal data, and the benefits this research offers. Data Storage and Retrieval: Spatio-temporal data tends to be very high-volume. Then, a second round of analysis can be done to pinpoint potential problems or opportunities.

Database 52

Database Java Education Data Collection 52

U-Next

AUGUST 11, 2022

Other skills this role requires are predictive analysis, data mining, mathematics, computation analysis, exploratory data analysis, deep learning systems, statistical tests, and statistical analysis. Also, experience is required in software development, data processes, and cloud platforms. .

Medical 52

Medical Computer Science Scala Machine Learning 52

Ascend.io

SEPTEMBER 14, 2023

Here are some examples of how Python can be applied to various facets of data engineering: Data Collection Web scraping has become an accessible task thanks to Python libraries like Beautiful Soup and Scrapy, empowering engineers to easily gather data from web pages.

Data Engineering 52

Data Engineering Data Engineer Python Engineering 52

Knowledge Hut

JULY 3, 2023

Data ingestion is the method of streaming a high volume of data from various different origins to your system. Due to the data ingestion process, you can perform various operations like data analysis, dashboarding and other analytical and business tools.

Data Ingestion 52

Data Ingestion Pipeline-centric Google Cloud Media 52

Ascend.io

NOVEMBER 21, 2023

The emergence of cloud data warehouses, offering scalable and cost-effective data storage and processing capabilities, initiated a pivotal shift in data management methodologies. The transformation of data occurs within the data warehouse itself, after the loading phase.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Knowledge Hut

OCTOBER 27, 2023

Personality Analysis System Personality Analysis System project is an exciting software engineering project that requires a good understanding of natural language processing, AI algorithms, and data analysis. cvtColor(image, cv2.COLOR_BGR2GRAY) COLOR_BGR2GRAY) _, thresh = cv2.threshold(gray_image, RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

Software Engineer 98

Software Engineer Software Engineering Coding Project 98

Knowledge Hut

APRIL 24, 2024

cvtColor(image, cv2.COLOR_BGR2GRAY) COLOR_BGR2GRAY) _, thresh = cv2.threshold(gray_image, threshold(gray_image, 127, 255, cv2.THRESH_BINARY) THRESH_BINARY) contours, _ = cv2.findContours(thresh, findContours(thresh, cv2.RETR_TREE, RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) CHAIN_APPROX_SIMPLE) max_area = 0 max_cnt = None for cnt in contours: area = cv2.contourArea(cnt)

Software Engineer 52

Software Engineer Software Engineering Coding Project 52

Knowledge Hut

MAY 31, 2023

Additionally, business intelligence engineers look after the proper storage of data so that they can be extracted later. Business intelligence engineers must have an analytical mind and the required skill set for data analysis. BI architects also prepare the methods and frameworks to store necessary data.

Business Intelligence 52

Business Intelligence BI Business Analyst Consulting 52

AltexSoft

JUNE 26, 2023

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. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

JUNE 9, 2021

Difference between Data Science and Data Engineering Data Science Data Engineering Data Science involves extracting information from raw data to derive business insights and values using statistical methods. Data Engineering is associated with data collecting, processing, analyzing, and cleaning data.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

ProjectPro

FEBRUARY 21, 2023

Due to the enormous amount of data being generated and used in recent years, there is a high demand for data professionals, such as data engineers, who can perform tasks such as data management, data analysis, data preparation, etc.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

MARCH 27, 2024

You can check out the Big Data Certification Online to have an in-depth idea about big data tools and technologies to prepare for a job in the domain. To get your business in the direction you want, you need to choose the right tools for big data analysis based on your business goals, needs, and variety.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

Knowledge Hut

FEBRUARY 15, 2023

Not very surprisingly, the amount of data used and shared between networks is infinite. This has led to data analysis being a vital element of most businesses. Data analysts are professionals who manage and analyze data that give insight into business goals and help align them. What is Data Analysis?

Data Cleanse 52

Data Cleanse Entertainment Business Intelligence Recruitment 52

Edureka

AUGUST 2, 2023

Their efforts make ensuring that data is accurate, dependable, and consistent, laying the groundwork for data analysis and decision-making. What does a Data Processing Analysts do ? A data processing analyst’s job description includes a variety of duties that are essential to efficient data management.

Data Process 52

Data Process Process Data Cleanse Data Mining 52

Knowledge Hut

FEBRUARY 7, 2023

These statements in a SAS program are broadly classified as data steps and procedures. 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.

Data Science 52

Data Science Datasets SQL Data Mining 52

Knowledge Hut

DECEMBER 26, 2023

However, as we progressed, data became complicated, more unstructured, or, in most cases, semi-structured. This mainly happened because data that is collected in recent times is vast and the source of collection of such data is varied, for example, data collected from text files, financial documents, multimedia data, sensors, etc.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

ProjectPro

JANUARY 25, 2022

One of the most in-demand technical skills these days is analyzing large data sets, and Apache Spark and Python are two of the most widely used technologies to do this. 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

U-Next

AUGUST 17, 2022

Because of this, all businesses—from global leaders like Apple to sole proprietorships—need Data Engineers proficient in SQL. NoSQL – This alternative kind of data storage and processing is gaining popularity. They’ll come up during your quest for a Data Engineer job, so using them effectively will be quite helpful.

Data Engineering 52

Data Engineering Data Engineer Pipeline-centric Database-centric 52

Edureka

FEBRUARY 27, 2023

BI is a broad term that covers a wide range of activities, including data analysis, reporting, and visualization. It can improve efficiency by automating report generation and data analysis tasks. BI can help you to gain a competitive advantage by helping you to identify trends and patterns in your industry.

Business Intelligence 52

Business Intelligence BI Data Mining Data Warehouse 52

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

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. Data Variety Hadoop stores structured, semi-structured and unstructured data.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

SEPTEMBER 26, 2021

Big Data Engineers are professionals who handle large volumes of structured and unstructured data effectively. They are responsible for changing the design, development, and management of data pipelines while also managing the data sources for effective data collection.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

U-Next

JUNE 29, 2022

Working with large amounts of data necessitates more preparation than working with less data. With so many varied data forms and formats, it’s critical to approach data analysis with a well-thought-out strategy that considers all data. Data ingestion can be divided into two categories: .

Big Data 40

Big Data Big Data Ecosystem Data Lake Raw Data 40

AltexSoft

SEPTEMBER 21, 2023

Logstash is a server-side data processing pipeline that ingests data from multiple sources, transforms it, and then sends it to Elasticsearch for indexing. Fluentd is a data collector and a lighter-weight alternative to Logstash. It is designed to unify data collection and consumption for better use and understanding.

Engineering 52

Engineering NoSQL Programming Language Java 52

AltexSoft

MAY 14, 2021

A growing number of companies now use this data to uncover meaningful insights and improve their decision-making, but they can’t store and process it by the means of traditional data storage and processing units. Key Big Data characteristics. Big Data analytics processes and tools. Data ingestion.

Big Data 78

Big Data Data Analytics IT NoSQL 78

AltexSoft

JUNE 7, 2021

The keyword here is distributed since the data quantities in question are too large to be accommodated and analyzed by a single computer. The framework provides a way to divide a huge data collection into smaller chunks and shove them across interconnected computers or nodes that make up a Hadoop cluster. Data storage options.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Data Engineering Podcast

JANUARY 28, 2018

So there was like the small scale, spreadsheet and manually updating data and spreadsheets, and then sending that off to visualize and to like, big fortune 500 companies that had data warehouses and full internal API’s that we got access to. And they that group basically does census data collection in slums all over the world.

Data 100

Data Project Electronics Data Management 100

ProjectPro

MARCH 17, 2014

Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Image Credit: twitter.com There are hundreds of companies like Facebook, Twitter, and LinkedIn generating yottabytes of data. The Hadoop ecosystem consists of a set of tools such as MapReduce, Hive, Pig, etc.

Hadoop 52

Hadoop Big Data Unstructured Data Retail 52

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

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

ProjectPro

MAY 31, 2021

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications. Visualizing Wikipedia Trends Big Data Project with Source Code.

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

AUGUST 21, 2015

IBM has a nice, simple explanation for the four critical features of big data: a) Volume –Scale of data b) Velocity –Analysis of streaming data c) Variety – Different forms of data d) Veracity –Uncertainty of data Here is an explanatory video on the four V’s of Big Data 3.

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

DECEMBER 17, 2021

Data science and artificial intelligence might be the buzzwords of recent times, but they are of no value without the right data backing them. The process of data collection has increased exponentially over the last few years. NoSQL databases are designed to store unstructured data like graphs, documents, etc.,

Data Science 52

Data Science SQL NoSQL Programming Language 52