Knowledge Hut

JANUARY 30, 2024

Whether you're a seasoned data scientist or just stepping into the world of data, come with me as we unravel the secrets of data extraction and learn how it empowers us to unleash the full potential of data. What is data extraction? What is the purpose of extracting data?

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Knowledge Hut

DECEMBER 21, 2023

This massive amount of data is referred to as “big data,” which comprises large amounts of data, including structured and unstructured data that has to be processed. To establish a career in big data, you need to be knowledgeable about some concepts, Hadoop being one of them. What is Hadoop?

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

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

AltexSoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Obviously, Big Data processing involves hundreds of computing units.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Monte Carlo

FEBRUARY 27, 2024

Right now, RAG is the essential technique to make GenAI models useful by giving an LLM access to an integrated, dynamic dataset while responding to prompts. But instead of integrating a dynamic database to an existing LLM, fine-tuning involves training an LLM on a smaller, task-specific, and labeled dataset.

Data Engineering 59

Data Engineering Data Engineer Engineering High Quality Data 59

Edureka

AUGUST 2, 2023

Python offers a strong ecosystem for data scientists to carry out activities like data cleansing, exploration, visualization, and modeling thanks to modules like NumPy, Pandas, and Matplotlib. It can be used for web scraping, machine learning, and natural language processing.

Programming Language 52

Programming Language Programming Scala Pharmaceutical 52

ProjectPro

JANUARY 31, 2023

Big Data is a collection of large and complex semi-structured and unstructured data sets that have the potential to deliver actionable insights using traditional data management tools. Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Towards Data Science

MARCH 5, 2024

The storage system is using Capacitor, a proprietary columnar storage format by Google for semi-structured data and the file system underneath is Colossus, the distributed file system by Google. In that case, queries are still processed using the BigQuery compute infrastructure but read data from GCS instead.

Bytes 70

Bytes Google Cloud Cloud Storage Utilities 70

AltexSoft

AUGUST 29, 2023

Another distinction is the ETL vs. ELT choice: In data warehouses, Extract and Transform processes usually occur before data is loaded into the warehouse. Many organizations also deploy data marts , which are dedicated storage repositories for specific business lines or workgroups. Structured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Edureka

FEBRUARY 8, 2024

Different instance types offer varying levels of compute power, memory, and storage, which directly influence tasks such as data processing, application responsiveness, and overall system throughput. Key Factors to Consider- When choosing an AWS instance type, several key factors should guide your decision-making process.

AWS 52

AWS NoSQL Deep Learning Datasets 52

Knowledge Hut

SEPTEMBER 26, 2023

Organisations are constantly looking for robust and effective platforms to manage and derive value from their data in the constantly changing landscape of data analytics and processing. These platforms provide strong capabilities for data processing, storage, and analytics, enabling companies to fully use their data assets.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Cloudera

NOVEMBER 15, 2021

In terms of representation, data can be broadly classified into two types: structured and unstructured. Structured data can be defined as data that can be stored in relational databases, and unstructured data as everything else. Data scrutiny.

Unstructured Data 88

Unstructured Data Pipeline-centric Database-centric Entertainment 88

AltexSoft

MAY 14, 2021

Not only does Big Data apply to the huge volumes of continuously growing data that come in different formats, but it also refers to the range of processes, tools, and approaches used to gain insights from that data. Key Big Data characteristics. Velocity is the speed at which the data is generated and processed.

Big Data 78

Big Data Data Analytics IT NoSQL 78

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. doc,docx), PDF files (.pdf),

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. If we look at history, the data that was generated earlier was primarily structured and small in its outlook.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Knowledge Hut

DECEMBER 26, 2023

Big Data is an immense amount of data that is constantly growing exponentially. Due to its vastness and complexity, no traditional data management system can adequately store or process this data. The New York Stock Exchange, which generates one terabyte of new trade data each day, is a classic example of big data.

Big Data 75

Big Data Data Mining Business Intelligence Machine Learning 75

AltexSoft

JULY 19, 2022

In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. There have been relational databases, data warehouses, data lakes, and even a combination of the latter two.

Architecture 52

Architecture Data Lake Medical Datasets 52

Knowledge Hut

OCTOBER 30, 2023

Data Validation: Help validate data against predefined business rules and ensure data quality. Documentation: Maintain documentation for reports, data sources, and data transformation processes. Manage data integration tasks, including data source connections and data transformation processes.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 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

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 HDFS master-slave structure works.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

NOVEMBER 15, 2021

It derives its name “Beam” which is from “Batch” + “Stream” from its functionalities for both batch and streaming the parallel processing pipelines for data. You can contribute to Apache Beam open-source big data project here: [link] 2.

Big Data 52

Big Data Project Metadata Programming Language 52

Rockset

AUGUST 2, 2023

This enrichment data has changing schemas and new data providers are constantly being added to enhance the insights, making it challenging for Windward to support using relational databases with strict schemas. The performance of Snowflake was evaluated on a Large virtual data warehouse that is $16/hr in AWS US-West.

Database-centric 52

Database-centric PostgreSQL Transportation Insurance 52

ProjectPro

JANUARY 19, 2022

Data engineering is a new and ever-evolving field that can withstand the test of time and computing developments. Companies frequently hire certified Azure Data Engineers to convert unstructured data into useful, structured data that data analysts and data scientists can use.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 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

ProjectPro

DECEMBER 7, 2021

Data Pipeline Tools AWS Data Pipeline Azure Data Pipeline Airflow Data Pipeline Learn to Create a Data Pipeline FAQs on Data Pipeline What is a Data Pipeline? A pipeline may include filtering, normalizing, and data consolidation to provide desired data.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59

AltexSoft

NOVEMBER 10, 2021

This enables different teams to use a single system to access all of the enterprise data for a range of projects, including data science, machine learning, and business intelligence. Let’s elaborate on this and figure out how a data lakehouse is different from its ancestors and name inspirers in more detail. Data warehouse.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

ProjectPro

AUGUST 11, 2021

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data is generally not loaded into a data warehouse unless a use case has been defined for the data.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 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

U-Next

AUGUST 8, 2022

This is a must-know language since it is the industry standard for communicating with relational databases. Data science specialists must be able to query databases, and a good grasp of SQL is essential for any aspiring Data Scientist. calculating the maximum and lowest values in a given data collection.

Data Science 40

Data Science Coding Programming Language Scala 40

AltexSoft

OCTOBER 8, 2021

In this article, we’re comparing several data integration tools against key criteria to help companies looking for ways to merge and centralize data make an informed choice. Data integration in a nutshell. Data integration process. Data integration tools and their main types.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

ProjectPro

NOVEMBER 22, 2021

What's the difference between an RDD, a DataFrame, and a DataSet? RDD- It is Spark's structural square. RDDs contain all datasets and dataframes. If a similar arrangement of data needs to be calculated again, RDDs can be efficiently reserved. When using a bigger dataset, the application fails due to a memory error.

Hadoop 52

Hadoop Python Datasets Metadata 52

ProjectPro

FEBRUARY 16, 2023

Data engineers are responsible for these data integration and ELT tasks, where the initial step requires extracting data from different types of databases/files, such as RDBMS, flat files, etc. Engineers can also use the "LOAD DATA INFILE" command to extract data from flat files like CSV or TXT.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

ProjectPro

MARCH 19, 2015

RDBMS is not always the best solution for all situations as it cannot meet the increasing growth of unstructured data. As data processing requirements grow exponentially, NoSQL is a dynamic and cloud friendly approach to dynamically process unstructured data with ease.IT

NoSQL 49

NoSQL Big Data SQL Database-centric 49

ProjectPro

JUNE 23, 2016

Sqoop is compatible with all JDBC compatible databases. Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Apache Sqoop uses Hadoop MapReduce to get data from relational databases and stores it on HDFS.

Hadoop 40

Hadoop MySQL Relational Database Java 40

ProjectPro

JULY 13, 2015

Large commercial banks like JPMorgan have millions of customers but can now operate effectively-thanks to big data analytics leveraged on increasing number of unstructured and structured data sets using the open source framework - Hadoop. JP Morgan has massive amounts of data on what its customers spend and earn.

Hadoop 52

Hadoop Big Data Data Analytics Banking 52

ProjectPro

AUGUST 24, 2016

The NOSQL column oriented database has experienced incredible popularity in the last few years. You might have come across several resources that explain HBase architecture and guide you through HBase installation process. The layout of HBase data model eases data partitioning and distribution across the cluster.

Architecture 40

Architecture IT Hadoop NoSQL 40