AltexSoft

AUGUST 29, 2023

The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. This article explains what a data lake is, its architecture, and diverse use cases. Data sources can be broadly classified into three categories.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

DECEMBER 29, 2023

Data Mining Data science field of study, data mining is the practice of applying certain approaches to data in order to get useful information from it, which may then be used by a company to make informed choices. It separates the hidden links and patterns in the data. Data mining's usefulness varies per sector.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

ProjectPro

OCTOBER 18, 2021

Machine Learning Projects are the key to understanding the real-world implementation of machine learning algorithms in the industry. To build such ML projects, you must know different approaches to cleaning raw data. To develop such algorithms, you need to have a thorough understanding of the following: a.

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

Knowledge Hut

DECEMBER 26, 2023

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. This is one of the major reasons behind the popularity of data science.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

ProjectPro

NOVEMBER 14, 2015

Hadoop can be used to carry out data processing using either the traditional (map/reduce) or Spark-based (providing an interactive platform to process queries in real-time) approach. Given a graphical relation between variables, an algorithm needs to be developed which predicts which two nodes are most likely to be connected?

Hadoop 52

Hadoop Project Big Data Healthcare 52

Snowflake

MARCH 30, 2023

Collecting, cleaning, and organizing data into a coherent form for business users to consume are all standard data modeling and data engineering tasks for loading a data warehouse. Based on Tecton blog So is this similar to data engineering pipelines into a data lake/warehouse?

Engineering 81

Engineering Raw Data Data Science Scala 81

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.

Data Process 52

Data Process Process Data Cleanse Data Mining 52

Edureka

JANUARY 18, 2024

For those looking to start learning in 2024, here is a data science roadmap to follow. What is Data Science? Data science is the study of data to extract knowledge and insights from structured and unstructured data using scientific methods, processes, and algorithms.

Data Science 40

Data Science Deep Learning NoSQL Machine Learning 40

Knowledge Hut

APRIL 25, 2024

Variety: Unstructured data, semi-structured data, and raw data are only a few examples of the variety of data kinds that exist. It is effective to use a recommendation engine that makes use of data filtering technologies that gather data and then filter it using algorithms.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

AltexSoft

JUNE 26, 2023

Data collection revolves around gathering raw data from various sources, with the objective of using it for analysis and decision-making. It includes manual data entries, online surveys, extracting information from documents and databases, capturing signals from sensors, and more.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 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. Why Is Big Data Analytics Important?

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

ProjectPro

MAY 20, 2015

It provides the first purpose-built Adaptive Data Preparation Solution(launched in 2013) for data scientist, IT teams, data curators, developers, and business analysts -to integrate, cleanse and enrich raw data into meaningful analytic ready big data that can power operational, predictive , ad-hoc and packaged analytics.

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

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. . SAS Institute developed this software.

Business Intelligence 40

Business Intelligence Raw Data Data Cleanse Data Analysis 40

Knowledge Hut

JANUARY 18, 2024

These streams basically consist of algorithms that seek to make either predictions or classifications by creating expert systems that are based on the input data. Even Email spam filters that we enable or use in our mailboxes are examples of weak AI where an algorithm is used to classify spam emails and move them to other folders.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

ProjectPro

AUGUST 11, 2021

This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data from data warehouses is queried using SQL.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Snowflake

JANUARY 18, 2023

Alignment of sequence data with a reference genome and variant-calling algorithms are key elements of primary and secondary genomic data analysis. The next step—tertiary analysis—involves analyzing large and dynamic collections of this preprocessed data, frequently packaged and distributed as compressed VCF files.

Pharmaceutical 83

Pharmaceutical AWS Java Healthcare 83

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 AWS Relational Database 52

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 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. Google BigQuery receives the structured data from workers.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

JANUARY 31, 2022

Provides Powerful Computing Resources for Data Processing Before inputting data into advanced machine learning models and deep learning tools, data scientists require sufficient computing resources to analyze and prepare it. A micro-partition's data size ranges from fifty MB to five hundred MB.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Knowledge Hut

JANUARY 11, 2024

Data science is the field of study that deals with a huge volume of data using modern technologically driven tools and techniques to find some sort of pattern and derive meaningful information out of it that eventually helps in business and financial decisions. Under this certification, you cover Python/R, statistics, and tableau.

Finance 93

Finance Data Science Programming Language Machine Learning 93

AltexSoft

MAY 12, 2023

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

AltexSoft

DECEMBER 15, 2021

On the surface, ML algorithms take the data, develop their own understanding of it, and generate valuable business insights and predictions — all without human intervention. It boosts the performance of ML specialists relieving them of repetitive tasks and enables even non-experts to experiment with smart algorithms.

Machine Learning 59

Machine Learning Deep Learning Algorithm Telecommunication 59

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. To build a big data project, you should always adhere to a clearly defined workflow.

Big Data 52

Big Data Coding Project Hadoop 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 Job site 15 nodes Runs Machine learning Algorithms 44 CDU now! 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 40

Hadoop Big Data Data Mining Retail 40

AltexSoft

MARCH 14, 2023

Data storage The tools mentioned in the previous section are instrumental in moving data to a centralized location for storage, usually, a cloud data warehouse, although data lakes are also a popular option. But this distinction has been blurred with the era of cloud data warehouses.

IT 59

IT Data Warehouse Data Governance Data Lake 59