Knowledge Hut

JANUARY 24, 2024

A significant part of their role revolves around collecting, cleaning, and manipulating data, as raw data is seldom pristine. In their quest for knowledge, data scientists meticulously identify pertinent questions that require answers and source the relevant data for analysis.

Database-centric 52

Database-centric Data Science Machine Learning Datasets 52

Grouparoo

JANUARY 11, 2022

The fundamental purpose of a data warehouse is the aggregation of information from diverse sources to inform data-driven decision-making processes. What is a Data Lake? There is no processing to integrate and manage data, including quality checks or detect inconsistencies, duplications, or discrepancies.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Knowledge Hut

MARCH 29, 2024

It helps you convert the raw data into actionable insights, streamlining the design workflow and promoting better decision-making. Through affinity mapping, you can even find patterns in your data by visually grouping related ideas or data points. Ensure that the data is comprehensive about the research objectives.

Process 52

Process Designing Unstructured Data Raw Data 52

Knowledge Hut

JANUARY 19, 2024

With businesses relying heavily on data, the demand for skilled data scientists has skyrocketed. In data science, we use various tools, processes, and algorithms to extract insights from structured and unstructured data. Coding Coding is the wizardry behind turning data into insights.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

Knowledge Hut

NOVEMBER 28, 2023

With a plethora of new technology tools on the market, data engineers should update their skill set with continuous learning and data engineer certification programs. What do Data Engineers Do? As a Data Engineer, you must: Work with the uninterrupted flow of data between your server and your application.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

U-Next

AUGUST 18, 2022

Data Science may combine arithmetic, business savvy, technologies, algorithm, and pattern recognition approaches. These factors all work together to help us uncover underlying patterns or observations in raw data that can be extremely useful when making important business choices.

Unstructured Data 40

Unstructured Data Medical Data Science Business Intelligence 40

AltexSoft

MAY 12, 2022

Audio data file formats. Similar to texts and images, audio is unstructured data meaning that it’s not arranged in tables with connected rows and columns. Audio data transformation basics to know. One of the largest audio data collections is AudioSet by Google. Audio data labeling.

Machine Learning 122

Machine Learning Building Datasets Healthcare 122

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

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. Who is a Data Scientist?

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

ProjectPro

JULY 3, 2015

.”- Henry Morris, senior VP with IDC SAP is considering Apache Hadoop as large scale data storage container for the Internet of Things (IoT) deployments and all other application deployments where data collection and processing requirements are distributed geographically.

Hadoop 40

Hadoop Big Data Data Solutions Unstructured Data 40

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer's primary responsibility is the construction and upkeep of a data warehouse. In this role, they would help the Analytics team become ready to leverage both structured and unstructured data in their model creation processes. They construct pipelines to collect and transform data from many sources.

Data Science 75

Data Science Data Mining Deep Learning Programming Language 75

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 76

Data Engineering Data Engineer Engineering Pipeline-centric 76

Edureka

AUGUST 2, 2023

Organisations and businesses are flooded with enormous amounts of data in the digital era. Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly. Data processing analysts can be useful in this situation. What does a Data Processing Analysts do ?

Data Process 52

Data Process Process Data Cleanse Data Mining 52

Data Engineering Weekly

MAY 8, 2023

Receipt table (later referred to as table_receipts_index): It turns out that all the receipts were manually entered into the system, which creates unstructured data that is error-prone. This data collection method was chosen because it was simple to deploy, with each employee responsible for their own receipts.

Process 52

Process Banking Raw Data Finance 52

Monte Carlo

FEBRUARY 15, 2023

This article will define in simple terms what a data warehouse is, how it’s different from a database, fundamentals of how they work, and an overview of today’s most popular data warehouses. What is a data warehouse? Cleaning Bad data can derail an entire company, and the foundation of bad data is unclean data.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

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. are accessible via URL.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

ProjectPro

SEPTEMBER 26, 2021

Automated tools are developed as part of the Big Data technology to handle the massive volumes of varied data sets. Big Data Engineers are professionals who handle large volumes of structured and unstructured data effectively.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 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. However, the vast volume of data will overwhelm you if you start looking at historical trends. Well, it surely is!

BI 52

BI ETL Tools Retail Healthcare 52

Rockset

DECEMBER 9, 2019

As a data engineer, my time is spent either moving data from one place to another, or preparing it for exposure to either reporting tools or front end users. As data collection and usage have become more sophisticated, the sources of data have become a lot more varied and disparate, volumes have grown and velocity has increased.

Data Engineering 40

Data Engineering Data Engineer Raw Data Engineering 40

AltexSoft

MAY 12, 2023

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

JANUARY 31, 2023

Big data enables businesses to get valuable insights into their products or services. Almost every company employs data models and big data technologies to improve its techniques and marketing campaigns. Most leading companies use big data analytical tools to enhance business decisions and increase revenues.

Big Data 52

Big Data Hadoop AWS Relational Database 52

AltexSoft

SEPTEMBER 23, 2021

A data hub, in turn, is rather a terminal or distribution station: It collects information only to harmonize it, and sends it to the required end-point systems. Data lake vs data hub. A data lake is quite opposite of a DW, as it stores large amounts of both structured and unstructured data.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

ProjectPro

NOVEMBER 30, 2021

Now that we have understood how much significant role data plays, it opens the way to a set of more questions like How do we acquire or extract raw data from the source? How do we transform this data to get valuable insights from it? Where do we finally store or load the transformed data?

Process 52

Process Data Pipeline Data Warehouse AWS 52

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.

Retail 52

Retail Data Science Computer Science Entertainment 52

AltexSoft

MAY 14, 2021

The process of identifying the sources and then getting Big Data varies from company to company. It’s worth noting though that data collection commonly happens in real-time or near real-time to ensure immediate processing.

Big Data 78

Big Data Data Analytics IT NoSQL 78

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

ProjectPro

AUGUST 16, 2021

A typical machine learning project involves data collection, data cleaning, data transformation, feature extraction, model evaluation approaches to find the best model fitting and hyper tuning parameters for efficiency. 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

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. A data engineer interacts with this warehouse almost on an everyday basis.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Knowledge Hut

APRIL 23, 2024

Data plays a crucial role in identifying opportunities for growth and decision-making in today's business landscape. Business intelligence collects techniques, tools, and methodologies organizations use to transform raw data into valuable information and meaningful insights. Automation can help businesses in several ways.

Business Intelligence 52

Business Intelligence BI Data Analysis Media 52

U-Next

SEPTEMBER 23, 2022

Previously, organizations dealt with static, centrally stored data collected from numerous sources, but with the advent of the web and cloud services, cloud computing is fast supplanting the traditional in-house system as a dependable, scalable, and cost-effective IT solution. It is not as simple as converting data into insights.

Big Data Ecosystem 40

Big Data Ecosystem Big Data Healthcare Data Lake 40

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40

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. How Big Data Works?

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

MARCH 14, 2014

Work on Interesting Big Data and Hadoop Projects to build an impressive project portfolio! How big data helps businesses? Companies using big data excel in sorting the growing influx of big data collected, filtering out the relevant information to draw deeper insights through big data analytics.

Hadoop 40

Hadoop Big Data Data Mining Retail 40