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.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Knowledge Hut

APRIL 26, 2024

Let's take a look at all the fuss about data science , its courses, and the path to the future. What is Data Science? In order to discover insights and then analyze multiple structured and unstructured data, Data Science requires the use of different instruments, algorithms and principles.

Data Science 52

Data Science Machine Learning Hadoop Programming Language 52

Knowledge Hut

DECEMBER 26, 2023

Leveraging Apache technologies like Hadoop, Cassandra, Avro, Pig, Mahout, Oozie, and Hive to encapsulate, split, and isolate Big Data and virtualize Big Data servers. Examining business cases, preparing, extracting, transforming, analyzing, and displaying data are steps in the big data analytics lifecycle.

Big Data 75

Big Data Data Mining Business Intelligence Machine Learning 75

Knowledge Hut

DECEMBER 26, 2023

If we look at history, the data that was generated earlier was primarily structured and small in its outlook. A simple usage of Business Intelligence (BI) would be enough to analyze such datasets. However, as we progressed, data became complicated, more unstructured, or, in most cases, semi-structured.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Grouparoo

NOVEMBER 16, 2021

This is where data transformation can come to the rescue. What is Data Transformation Simply speaking, the data transformation definition is the process of converting data from diverse sources into a standard format that supports its analysis. One of the leaders in the space focused on data transforms is dbt.

Data Mining 52

Data Mining Raw Data ETL Tools Unstructured Data 52

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. Kicking off a big data analytics project is always the most challenging part.

Big Data 52

Big Data Coding Project Hadoop 52

Ascend.io

DECEMBER 14, 2022

In the hopes of resolving this issue, ETL tasks that update hundreds or millions of data warehouse tables frequently take place at night. But in a world that favors the here and now, ETL processes lack in the area of providing analysts with new, fresh data. The same principle guides data transformations in the ELT process.

Data Integration 52

Data Integration Raw Data Data Consolidation Data Warehouse 52

Tweag

APRIL 19, 2023

The MedTech industry is buzzing thanks to a continuous stream of innovation, promising to be more precise, efficient and accessible than ever. Although it has Python bindings, OpenSlide is implemented in C and reads files using standard OS file handlers, however our data sits on cloud storage that is accessible via HTTP.

Medical 59

Medical Process Cloud Bytes 59

ProjectPro

MARCH 17, 2021

What follows is a straightforward and easy-to-understand primer on “Deep Learning” vs “Machine Learning” Table of Contents Deep Learning vs Machine Learning – Understanding the Differences Machine Learning vs Deep Learning – The Definition What is Machine Learning? What is Deep Learning?

Deep Learning 52

Deep Learning Machine Learning Algorithm Datasets 52

Knowledge Hut

JUNE 20, 2023

Data Engineer vs Machine Learning Engineer While there are similarities between a data engineer and a machine learning engineer, both play a key role in the technological world. Factors Data Engineer Machine Learning Definition Data engineers create, maintain, and optimize data infrastructure for data.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Meltano

OCTOBER 5, 2022

To reduce development time and increase data reliability, DataOps engineers automate manual processes, such as data extraction and testing. Managing the production of data pipelines. A DataOps engineer provides organizations with access to structured datasets and analytics they will further analyze and derive insights from.

Engineering 52

Engineering Raw Data Data Pipeline ETL Tools 52

ProjectPro

OCTOBER 18, 2021

Datasets like Google Local, Amazon product reviews, MovieLens, Goodreads, NES, Librarything are preferable for creating recommendation engines using machine learning models. They have a well-researched collection of data such as ratings, reviews, timestamps, price, category information, customer likes, and dislikes.

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

ProjectPro

JUNE 9, 2021

As we proceed further into the blog, you will find some statistics on data engineering vs. data science jobs and data engineering vs. data science salary, along with an in-depth comparison between the two roles- data engineer vs. data scientist. vs. What does a Data Engineer do?

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

ProjectPro

JULY 27, 2021

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

NOVEMBER 30, 2021

If you are into Data Science or Big Data, you must be familiar with an ETL pipeline. This guide provides definitions, a step-by-step tutorial, and a few best practices to help you understand ETL pipelines and how they differ from data pipelines. It is the most feasible option when the data size is huge.

Process 52

Process Data Pipeline Data Warehouse AWS 52

ProjectPro

NOVEMBER 30, 2021

Data mining is sometimes also used as a prerequisite for building a machine learning model. Get FREE Access to Machine Learning Example Codes for Data Cleaning, Data Munging, and Data Visualization What is Machine Learning? But they both use data to a different extent and to attain all together different goals.

Data Mining 52

Data Mining Machine Learning Data Science Algorithm 52

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.

Hadoop 40

Hadoop Big Data Data Solutions Unstructured Data 40

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. Outliers in the dataset are dropped, and null values are imputed.

Machine Learning 40

Machine Learning Coding Project Deep Learning 40

ProjectPro

JULY 13, 2015

With more than 150 petabytes of data, approximately 3.5 billion user accounts and 30,000 databases, JPMorgan Chase is definitely a name to reckon with in the financial sector. JP Morgan has massive amounts of data on what its customers spend and earn. Hadoop allows us to store data that we never stored before.

Hadoop 52

Hadoop Big Data Data Analytics Banking 52

ProjectPro

FEBRUARY 21, 2023

Although challenging, a career in data engineering can be rewarding. Data engineers and their skills play a crucial role in the success of an organization by making it easier for data scientists , data analysts , and decision-makers to access the data they need to do their jobs.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

ProjectPro

AUGUST 11, 2021

The data warehouse layer consists of the relational database management system (RDBMS) that contains the cleaned data and the metadata, which is data about the data. The RDBMS can either be directly accessed from the data warehouse layer or stored in data marts designed for specific enterprise departments.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

ProjectPro

JUNE 4, 2015

HDFS in Hadoop architecture provides high throughput access to application data and Hadoop MapReduce provides YARN based parallel processing of large data sets. The basic principle of working behind Apache Hadoop is to break up unstructured data and distribute it into many parts for concurrent data analysis.

Hadoop 52

Hadoop Architecture IT Java 52

ProjectPro

OCTOBER 20, 2021

AutoKeras focuses on making machine learning and deep learning more accessible with the help of Neural Architecture Search. Auto-Weka : Weka is a top-rated java-based machine learning software for data exploration. This will give us access to the latest security, technology, reduced cost, and even world-class APIs.

Machine Learning 52

Machine Learning Algorithm Government Data Science 52

ProjectPro

MAY 23, 2015

With more than 245 million customers visiting 10,900 stores and with 10 active websites across the globe, Walmart is definitely a name to reckon with in the retail sector. petabytes of unstructured data from 1 million customers every hour. petabytes of unstructured data from 1 million customers every hour.

Big Data 52

Big Data Data Analysis Hadoop Retail 52

ProjectPro

JUNE 18, 2015

For Silicon Valley startups launching a big data platform, the best way to reduce expenses is to pay remote workers so that they can distribute tasks to people who have internet access anywhere in the world. Enterprises that completely crowdsource data to make critical business decisions, definitely does have some loopholes.

Big Data 52

Big Data Process Data Cleanse Data Analytics 52

ProjectPro

MARCH 16, 2015

McKinsey projects that the use of Big Data in healthcare can reduce the healthcare data management expenses by $300 billion -$500 billion. Big Data in healthcare originates from the large electronic health datasets – these datasets are very difficult to manage with the conventional hardware and software.

Healthcare 40

Healthcare Big Data Project Hospitality 40

ProjectPro

MARCH 21, 2016

Mainframe data cannot be ignored because it drives mission critical applications across myriad industries. The answer is definitely a resounding YES. Using Hadoop distributed processing framework to offload data from the legacy Mainframe systems, companies can optimize the cost involved in maintaining Mainframe CPUs.

Hadoop 40

Hadoop Insurance Big Data Retail 40

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. Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization How Online Dating Alogirthms work? Image Credit: linkurio.us

Big Data 52

Big Data Data Analysis Algorithm Hadoop 52

ProjectPro

JUNE 2, 2015

We have to find the right correlation patterns for all our forward memories and incoming data to predict upcoming malfunctions and their consequences."- Business win online when they use hard-to-copy technology to deliver a superior customer experience through mining larger and larger datasets.”-

Big Data 40

Big Data Hadoop Banking Retail 40

AltexSoft

JUNE 26, 2023

We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection? It’s the first and essential stage of data-related activities and projects, including business intelligence , machine learning , and big data analytics.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

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

AltexSoft

NOVEMBER 1, 2023

NER for structuring unstructured data NER plays a pivotal role in converting unstructured text into structured data. By doing so, NER transforms vast amounts of textual content into organized datasets, ready for further analysis. Why use it? Several neural network architectures are prominent in the NER domain.

Deep Learning 52

Deep Learning Machine Learning Datasets Algorithm 52

AltexSoft

JULY 29, 2022

Apache Hadoop is an open-source Java-based framework that relies on parallel processing and distributed storage for analyzing massive datasets. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics. How data engineering works under the hood.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

DataKitchen

APRIL 13, 2021

Because it is such a new category, both overly narrow and overly broad definitions of DataOps abound. DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. Meta-Orchestration . Other Vendors Talking DataOps.

Consulting 120

Consulting Machine Learning Data Science Data Pipeline 120

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

U-Next

AUGUST 3, 2022

Data Scientist roles and responsibilities have become increasingly challenging, fun, and worthwhile. . Although the term “Data Science” might imply various things to various individuals, it is essentially the use of data to provide answers to inquiries. What are Data Scientist roles?

Retail 52

Retail Data Science Computer Science Entertainment 52

AltexSoft

NOVEMBER 23, 2021

Not to mention that additional sources are constantly being added through new initiatives like big data analytics , cloud-first, and legacy app modernization. To break data silos and speed up access to all enterprise information, organizations can opt for an advanced data integration technique known as data virtualization.

Process 69

Process Data Lake Metadata Data Warehouse 69