ProjectPro

FEBRUARY 8, 2023

Do ETL and data integration activities seem complex to you? Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4 Businesses are leveraging big data now more than ever.

AWS 98

AWS Scala Metadata Data Lake 98

Cloudera

SEPTEMBER 15, 2022

Mark: While most discussions of modern data platforms focus on comparing the key components, it is important to understand how they all fit together. The collection of source data shown on your left is composed of both structured and unstructured data from the organization’s internal and external sources.

Data Lake 83

Data Lake Analytics Application Cloud Storage Architecture 83

Striim

SEPTEMBER 11, 2024

Third-Party Data: External data sources that your company does not collect directly but integrates to enhance insights or support decision-making. These data sources serve as the starting point for the pipeline, providing the raw data that will be ingested, processed, and analyzed.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

ProjectPro

FEBRUARY 16, 2023

Business Intelligence and Artificial Intelligence are popular technologies that help organizations turn raw data into actionable insights. While both BI and AI provide data-driven insights, they differ in how they help businesses gain a competitive edge in the data-driven marketplace.

Business Intelligence 52

Business Intelligence BI Data Mining Algorithm 52

Databand.ai

JULY 19, 2023

The Transform Phase During this phase, the data is prepared for analysis. This preparation can involve various operations such as cleaning, filtering, aggregating, and summarizing the data. The goal of the transformation is to convert the raw data into a format that’s easy to analyze and interpret.

Data Cleanse 52

Data Cleanse Data Storage Raw Data Data Warehouse 52

DareData

JULY 5, 2023

If you work at a relatively large company, you've seen this cycle happening many times: Analytics team wants to use unstructured data on their models or analysis. For example, an industrial analytics team wants to use the logs from raw data.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

Edureka

AUGUST 2, 2023

Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly. Data processing analysts can be useful in this situation. Let’s take a deep dive into the subject and look at what we’re about to study in this blog: Table of Contents What Is Data Processing Analysis?

Data Process 52

Data Process Process Data Cleanse Data Mining 52

Sync Computing

NOVEMBER 7, 2024

Despite these limitations, data warehouses, introduced in the late 1980s based on ideas developed even earlier, remain in widespread use today for certain business intelligence and data analysis applications. While data warehouses are still in use, they are limited in use-cases as they only support structured data.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Unstructured Data 52

ProjectPro

JANUARY 27, 2023

You have probably heard the saying, "data is the new oil". It is extremely important for businesses to process data correctly since the volume and complexity of raw data are rapidly growing. Data Integration - ETL processes can be leveraged to integrate data from multiple sources for a single 360-degree unified view.

BI 52

BI ETL Tools Retail Healthcare 52

Rockset

DECEMBER 9, 2019

This obviously introduces a number of problems for businesses who want to make sense of this data because it’s now arriving in a variety of formats and speeds. To solve this, businesses employ data lakes with staging areas for all new data. This is where technologies like Rockset can help.

Data Engineer 40

Data Engineer Data Engineering Engineering Raw Data 40

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

AltexSoft

MAY 14, 2021

Modern technologies allow gathering both structured (data that comes in tabular formats mostly) and unstructured data (all sorts of data formats) from an array of sources including websites, mobile applications, databases, flat files, customer relationship management systems (CRMs), IoT sensors, and so on.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Monte Carlo

APRIL 1, 2021

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. Here’s where data catalogs fall short and how data discovery platforms and tools can help ensure your data lake doesn’t turn into a data swamp.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Government 52

Knowledge Hut

JANUARY 24, 2024

Much like intrepid adventurers venturing into the vast unknown, data scientists embark on a journey through the intricate maze of data, driven by the quest to unearth hidden treasures of insight. A significant part of their role revolves around collecting, cleaning, and manipulating data, as raw data is seldom pristine.

Database-centric 52

Database-centric Data Science Machine Learning Algorithm 52

Edureka

SEPTEMBER 23, 2024

What is Data Science? Data Science is an applied science that deals with the process of obtaining valuable information from structured and unstructured data. They use various tools, techniques, and methodologies borrowed from statistics, mathematics computer science to analyze large amounts of data.

Data Science 40

Data Science Data Mining Computer Science Finance 40

U-Next

AUGUST 18, 2022

Additionally, if you’re getting ready for an interview session as a Data Scientist, you must know all Data Scientists’ traits. We’ll cover all you need to understand, like what does a Data Scientist do ? Can a Data Scientist work from home ? What Is Data Science Course?

Unstructured Data 40

Unstructured Data Data Science Medical Business Intelligence 40

ProjectPro

JUNE 9, 2021

This blog on Data Science vs. Data Engineering presents a detailed comparison between the two domains. Data Science- Definition Data Science is an interdisciplinary branch encompassing data engineering and many other fields. A data scientist may not always be presented with a business problem to solve.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Science 52

Edureka

JANUARY 18, 2024

It also discusses available resources and tools, and the current data science landscape. For those looking to start learning in 2024, here is a data science roadmap to follow. What is Data Science? Exploratory Data Analysis (EDA Learn how to summarize and visualize data to identify trends and connections.

Data Science 40

Data Science Deep Learning Machine Learning NoSQL 40

ProjectPro

JANUARY 31, 2023

If you're looking to break into the exciting field of big data or advance your big data career, being well-prepared for big data interview questions is essential. Get ready to expand your knowledge and take your big data career to the next level! But the concern is - how do you become a big data professional?

Big Data 52

Big Data Hadoop Relational Database AWS 52

Monte Carlo

AUGUST 31, 2023

In many ways, the cloud makes data easier to manage, more accessible to a wider variety of users, and far faster to process. Not long after data warehouses moved to the cloud, so too did data lakes (a place to transform and store unstructured data), giving data teams even greater flexibility when it comes to managing their data assets.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Knowledge Hut

JULY 4, 2023

The rising demand for data analysts along with the increasing salary potential of these roles is making this an increasingly attractive field. But which are the highest-paying data analytics jobs available? This blog lists some of the most lucrative positions for aspiring data analysts. Build data systems and pipelines.

Data Analytics 52

Data Analytics Data Architect Data Science Transportation 52

Knowledge Hut

JANUARY 25, 2024

It doesn't matter if you're a data expert or just starting out; knowing how to clean your data is a must-have skill. The future is all about big data. This blog is here to help you understand not only the basics but also the cool new ways and tools to make your data squeaky clean.

Data Cleanse 52

Data Cleanse Datasets Data Preparation Data Science 52

ProjectPro

MAY 20, 2015

There are several big data and business analytics companies that offer a novel kind of big data innovation through unprecedented personalization and efficiency at scale. Which big data analytic companies are believed to have the biggest potential?

Big Data 40

Big Data Hadoop Business Analyst Data Analytics 40

ProjectPro

JULY 27, 2021

This blog is your one-stop solution for the top 100+ Data Engineer Interview Questions and Answers. In this blog, we have collated the frequently asked data engineer interview questions based on tools and technologies that are highly useful for a data engineer in the Big Data industry.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

ProjectPro

MARCH 23, 2015

The partnership among these technologies added value to the processing, managing and storage of Semi Structured, Structured and Unstructured Data in the Hadoop Cluster for these data giants. Approximately people spend 700 billion minutes on Facebook per month and this data is said to double semi annually.

Hadoop 40

Hadoop Big Data Architecture Kafka 40

ProjectPro

OCTOBER 18, 2021

To build such ML projects, you must know different approaches to cleaning raw data. From the outset of machine learning, it was challenging to work with unstructured data (image dataset) and transform it into structured data (texts). You have to use libraries like Dora, Scrubadub, Pandas, NumPy, etc.,

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

ProjectPro

AUGUST 24, 2021

Nevertheless, that is not the only job in the data world. Data professionals who work with raw data like data engineers, data analysts, machine learning scientists , and machine learning engineers also play a crucial role in any data science project. How do I create a Data Engineer Portfolio?

Data Engineer 52

Data Engineer Data Engineering Coding Project 52

ProjectPro

AUGUST 16, 2021

NLP projects are a treasured addition to your arsenal of machine learning skills as they help highlight your skills in really digging into unstructured data for real-time data-driven decision making. Topic Modelling Topic modelling is the inference of main keywords or topics from a large set of data.

Machine Learning 40

Machine Learning Coding Project Deep Learning 40

U-Next

AUGUST 3, 2022

A high-ranking expert is known as a “Data Scientist” who works with big data and has the mathematics, economic, technical, analytic, and technological abilities necessary to cleanse, analyse and evaluate organised and unstructured data to help organisations make more informed decisions.

Data Science 52

Data Science Retail Computer Science Entertainment 52

ProjectPro

MAY 31, 2021

Ace your big data interview by adding some unique and exciting Big Data projects to your portfolio. This blog lists over 20 big data projects you can work on to showcase your big data skills and gain hands-on experience in big data tools and technologies. are examples of semi-structured data.

Big Data 52

Big Data Coding Project Hadoop 52

AltexSoft

DECEMBER 15, 2021

feature engineering or feature extraction when useful properties are drawn from raw data and transformed into a desired form, and. The technology supports tabular, image, text, and video data, and also comes with an easy-to-use drag-and-drop tool to engage people without ML expertise. Source: Google Cloud Blog.

Machine Learning 59

Machine Learning Deep Learning Algorithm Telecommunication 59

Knowledge Hut

APRIL 23, 2024

Business intelligence collects techniques, tools, and methodologies organizations use to transform raw data into valuable information and meaningful insights. So, BI empowers businesses to understand their respective customers, make data-driven decisions, and analyze market trends.

Business Intelligence 52

Business Intelligence BI Data Analysis Media 52

ProjectPro

MARCH 14, 2014

Online FM Music 100 nodes, 8 TB storage Calculation of charts and data testing 16 IMVU Social Games Clusters up to 4 m1.large Hadoop is used at eBay for Search Optimization and Research. 12 Cognizant IT Consulting Per client requirements Client projects in finance, telecom and retail.

Hadoop 40

Hadoop Big Data Data Mining Retail 40