Knowledge Hut

MAY 31, 2023

These projects typically involve a collaborative team of software developers, data scientists, machine learning engineers, and subject matter experts. The development process may include tasks such as building and training machine learning models, data collection and cleaning, and testing and optimizing the final product.

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Project Healthcare Deep Learning Transportation 96

AltexSoft

JUNE 7, 2021

Apache Hadoop is an open-source framework written in Java for distributed storage and processing of huge datasets. The keyword here is distributed since the data quantities in question are too large to be accommodated and analyzed by a single computer. A powerful Big Data tool, Apache Hadoop alone is far from being almighty.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Knowledge Hut

JANUARY 18, 2024

This field uses several scientific procedures to understand structured, semi-structured, and unstructured data. It entails using various technologies, including data mining, data transformation, and data cleansing, to examine and analyze that data. Get to know more about SQL for data science.

Software Engineering 97

Software Engineering Software Engineer Data Science Engineering 97

Knowledge Hut

JULY 28, 2023

Data Types and Dimensionality ML algorithms work well with structured and tabular data, where the number of features is relatively small. DL models excel at handling unstructured data such as images, audio, and text, where the data has a large number of features or high dimensionality.

Deep Learning 52

Deep Learning Machine Learning Unstructured Data Algorithm 52

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

Knowledge Hut

APRIL 23, 2024

Big data has revolutionized the world of data science altogether. With the help of big data analytics, we can gain insights from large datasets and reveal previously concealed patterns, trends, and correlations. Learn more about the 4 Vs of big data with examples by going for the Big Data certification online course.

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Big Data Media Datasets Unstructured Data 52

Knowledge Hut

DECEMBER 26, 2023

These skills are essential to collect, clean, analyze, process and manage large amounts of data to find trends and patterns in the dataset. The dataset can be either structured or unstructured or both. In this article, we will look at some of the top Data Science job roles that are in demand in 2024.

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Data Science BI Business Intelligence Machine Learning 97

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.

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Process Banking Raw Data Finance 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.

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Big Data Data Analytics IT NoSQL 78

Netflix Tech

APRIL 26, 2022

Since we train our models on several weeks of data, this method is slow for us as we will have to wait for several weeks for the data collection. The Iceberg table created by Keystone contains large blobs of unstructured data. As our label dataset was also random, presorting facts data also did not help.

Metadata 76

Metadata Datasets Machine Learning Designing 76

ProjectPro

JULY 3, 2015

The maximum value of big data can be extracted by integrating the in-memory processing capabilities of SAP HANA (High Performance Analytic Appliance) and the ability of Hadoop to store large unstructured datasets. “With Big Data, you’re getting into streaming data and Hadoop. .”-

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Hadoop Big Data Data Solutions Unstructured Data 40

Knowledge Hut

DECEMBER 26, 2023

An information and computer scientist, database and software programmer, curator, and knowledgeable annotator are all examples of data scientists. They are all crucial for the administration of digital data collection to be successful. In the twenty-first century, data science is regarded as a profitable career.

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Data Science Unstructured Data Medical Healthcare 52

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 Relational Database AWS 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? Data can be loaded in batches or can be streamed in near real-time.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Striim

OCTOBER 11, 2024

Whether you’re in the healthcare industry or logistics, being data-driven is equally important. Here’s an example: Suppose your fleet management business uses batch processing to analyze vehicle data. Cloud-based data pipelines offer agility and elasticity, enabling businesses to adapt to trends without extensive planning.

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 52

Knowledge Hut

JULY 26, 2023

Consider exploring relevant Big Data Certification to deepen your knowledge and skills. What is Big Data? Big Data is the term used to describe extraordinarily massive and complicated datasets that are difficult to manage, handle, or analyze using conventional data processing methods.

Big Data 52

Big Data Data Cleanse Retail Healthcare 52

Knowledge Hut

JANUARY 24, 2024

This blog offers an exclusive glimpse into the daily rituals, challenges, and moments of triumph that punctuate the professional journey of a data scientist. The primary objective of a data scientist is to analyze complex datasets to uncover patterns, trends, and valuable information that can aid in informed decision-making.

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Database-centric Data Science Machine Learning Algorithm 52

Knowledge Hut

JUNE 23, 2023

Data warehousing to aggregate unstructured data collected from multiple sources. Data architecture to tackle datasets and the relationship between processes and applications. You should be well-versed in Python and R, which are beneficial in various data-related operations. What is COSHH?

Data Engineering 52

Data Engineering Data Engineer Engineering NoSQL 52

ProjectPro

MAY 23, 2015

2014 Kaggle Competition Walmart Recruiting – Predicting Store Sales using Historical Data Description of Walmart Dataset for Predicting Store Sales What kind of big data and hadoop projects you can work with using Walmart Dataset? petabytes of unstructured data from 1 million customers every hour.

Big Data 52

Big Data Data Analysis Hadoop Retail 52

AltexSoft

FEBRUARY 21, 2023

Data relevance. Including irrelevant data in the training dataset can make the model overly complex, as it tries to learn patterns that don’t actually fit the task. Just as bad data quality and scarcity, irrelevance can cause the model to make incorrect predictions when presented with new, unseen data.

Hospitality 52

Hospitality Algorithm Datasets Machine Learning 52

Knowledge Hut

JANUARY 30, 2024

In summary, data extraction is a fundamental step in data-driven decision-making and analytics, enabling the exploration and utilization of valuable insights within an organization's data ecosystem. What is the purpose of extracting data? The process of discovering patterns, trends, and insights within large datasets.

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ETL Tools Database-centric Data Mining Raw Data 52

Edureka

AUGUST 2, 2023

Data processing analysts are experts in data who have a special combination of technical abilities and subject-matter expertise. They are essential to the data lifecycle because they take unstructured data and turn it into something that can be used. What does a Data Processing Analysts do ?

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Data Process Process Data Cleanse Data Mining 52

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 98

Data Science Data Mining Deep Learning Programming Language 98

Ascend.io

NOVEMBER 21, 2023

Extract The initial stage of the ELT process is the extraction of data from various source systems. This phase involves collecting raw data from the sources, which can range from structured data in SQL or NoSQL servers, CRM and ERP systems, to unstructured data from text files, emails, and web pages.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

AltexSoft

APRIL 27, 2023

As the company explains , it can be compared to weather models considering a large amount of data like air pressure, wind speeds, and moisture to help meteorologists predict the weather. With the help of this platform, Moderna is able to conduct analysis of in-house data (clinical operations, gender, risk groups, etc.)

Data Analytics 52

Data Analytics Pharmaceutical Medical Manufacturing 52

Knowledge Hut

JUNE 20, 2023

Additionally, they create and test the systems necessary to gather and process data for predictive modelling. Data engineers play three important roles: Generalist: With a key focus, data engineers often serve in small teams to complete end-to-end data collection, intake, and processing.

Machine Learning 52

Machine Learning Data Engineer Data Engineering Engineering 52

ProjectPro

APRIL 14, 2015

Dating sites need to generate as much online dating data as possible for more probability of success in matching up partners who like each other. Dataset of eHarmony is greater than 4 TB of data, photos excluded. The data collected is sorted by specialized analysis algorithms which help users find a perfect match.

Big Data 52

Big Data Data Analysis Algorithm Hadoop 52

U-Next

AUGUST 11, 2022

Deep Learning is an AI Function that involves imitating the human brain in processing data and creating patterns for decision-making. It’s a subset of ML which is capable of learning from unstructured data. Why Should You Pursue A Career In Artificial Intelligence? There are excellent career opportunities in AI.

Medical 52

Medical Computer Science Machine Learning Scala 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. That's the promise of a career in data science. Implementing machine learning magic.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

ProjectPro

AUGUST 9, 2021

Top 20 Python Projects for Data Science Without much ado, it’s time for you to get your hands dirty with Python Projects for Data Science and explore various ways of approaching a business problem for data-driven insights. 1) Music Recommendation System on KKBox Dataset Music in today’s time is all around us.

Data Science 52

Data Science Python Project Datasets 52

DareData

JULY 5, 2023

We've seen this happen in dozens of our customers: data lakes serve as catalysts that empower analytical capabilities. 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. And what is the reason for that?

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

ProjectPro

JUNE 18, 2015

said Martha Crow, Senior VP of Global Testing at Lionbridge Big data is all the rage these days as various organizations dig through large datasets to enhance their operations and discover novel solutions to big data problems. Organizations need to collect thousands of data points to meet large scale decision challenges.

Big Data 52

Big Data Process Data Cleanse Data Analytics 52

ProjectPro

NOVEMBER 30, 2021

For instance, specify the list of country codes allowed in a country data field. Connectors to Extract data from sources and standardize data: For extracting structured or unstructured data from various sources, we will need to define tools or establish connectors that can connect to these sources.

Process 52

Process Data Pipeline Data Warehouse AWS 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 Engineer 52

Data Engineer Data Engineering Engineering Generalist 52

AltexSoft

NOVEMBER 23, 2021

Data virtualization architecture example. The responsibility of this layer is to access the information scattered across multiple source systems, containing both structured and unstructured data , with the help of connectors and communication protocols. Data virtualization platforms can link to different data sources including.

Process 69

Process Data Lake Metadata Data Warehouse 69

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 Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

ProjectPro

AUGUST 24, 2021

Explore different types of Data Formats: A data engineer works with various dataset formats like.csv,josn,xlx, etc. They are also often expected to prepare their dataset by web scraping with the help of various APIs. Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data.

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Data Engineer Data Engineering Coding Project 52