Knowledge Hut

APRIL 19, 2023

Levels of Data Aggregation Now lets look at the levels of data aggregation Level 1: At this level, unprocessed data are collected from various sources and put in one source. Level 2: At this stage, the raw data is processed and cleaned to get rid of inconsistent data, duplicates values, and error in datatype.

Process 59

Process Data Mining Aggregated Data Portfolio 59

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

Knowledge Hut

APRIL 25, 2024

Industries, where the application of spatial data science will expand have a wide range of verticals, including real estat e, cities and governments, management consulting, utilities, retails, telecommunication, green energy, and many more. Big Data Analytics Big data analytics has revolutionized many industries like no other.

Data Science 52

Data Science Telecommunication Transportation Big Data 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. .

Business Intelligence 40

Business Intelligence Raw Data Data Cleanse Data Analysis 40

Ascend.io

JULY 28, 2023

Ingestion: Your data pipeline architecture should anticipate a wide variety of raw data sources to be incorporated into the pipeline. These include internal sources, operational systems, the databases and files provided by business partners, and third-party sources from regulators, agencies, and data aggregators.

Data Pipeline 52

Data Pipeline Architecture Lambda Architecture Data Architecture 52

Edureka

FEBRUARY 18, 2023

BI can help organizations turn raw data into meaningful insights, enabling better decision-making, optimizing operations, enhancing customer experiences, and providing a strategic advantage. However, with such a vast amount of information available, it can be challenging to extract valuable insights and make sense of it all.

Business Intelligence 52

Business Intelligence BI SQL Data Analysis 52

phData: Data Engineering

SEPTEMBER 27, 2024

Real-world example: Imagine you’re modeling customer data for an omnichannel retail brand. This separation allows for a clear distinction between data acquisition and data modeling. The raw data is right there, ready to be reprocessed. All this raw data goes into your persistent stage.

Data 52

Data Raw Data Data Lake Architecture 52

Knowledge Hut

DECEMBER 29, 2023

Learning Outcomes: You will understand the processes and technology necessary to operate large data warehouses. Engineering and problem-solving abilities based on Big Data solutions may also be taught. It might also be industry-specific, such as the healthcare or financial industries, for example.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

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 Relational Database AWS 52

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. Also, explore other alternatives like Apache Hadoop and Spark RDD.

Data Engineer 52

Data Engineer Data Engineering Coding Project 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

The following duties are frequently handled by Data Scientists, even though each data research situation is unique and their tasks change based on the project. Gathering data Any Data Science experiment must include data collecting since, without data to work with, one cannot be a Data Scientist.

Data Science 52

Data Science Retail Computer Science Entertainment 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 Engineer Data Engineering Engineering 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 Engineer 98

Data Engineer Data Engineering Engineering Pipeline-centric 98

ProjectPro

AUGUST 21, 2015

How big data analysis helps businesses increase their revenue? Data that can be stored in traditional database systems in the form of rows and columns, for example, the online purchase transactions can be referred to as Structured Data. are all examples of unstructured data. Give example. If yes, then explain how.

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

MARCH 14, 2014

As the big data boom spreads globally, we at ProjectPro describe on how big data helps business across different industries and the companies using big data that stand to gain the most from implementing big data initiatives. Work on Interesting Big Data and Hadoop Projects to build an impressive project portfolio!

Hadoop 40

Hadoop Big Data Data Mining Retail 40