phData: Data Engineering

SEPTEMBER 19, 2023

This blog will guide you through the best data modeling methodologies and processes for your data lake, helping you make informed decisions and optimize your data management practices. What is a Data Lake? What are Data Modeling Methodologies, and Why Are They Important for a Data Lake?

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Knowledge Hut

MARCH 28, 2024

Now you might be thinking about what a data structure is, well it is the specialized way of storing and arranging data in the computer’s memory, allowing for efficient retrieval, manipulation and utilization. Learning data structures is like understanding computer language.

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Algorithm Java Utilities Data 52

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. 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. Structured data sources.

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Knowledge Hut

JULY 24, 2023

NoSQL Databases NoSQL databases are non-relational databases (that do not store data in rows or columns) more effective than conventional relational databases (databases that store information in a tabular format) in handling unstructured and semi-structured data. It is utilized for all types of storage and processing needs.

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Database NoSQL Management Relational Database 52

Knowledge Hut

NOVEMBER 3, 2023

MongoDB is used for data science, meaning that we utilize the capabilities of this NoSQL database system as part of our data analysis and data modeling processes, which fall under the realm of data science. There are several benefits to MongoDB for data science operations. Why Use MongoDB for Data Science?

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Monte Carlo

AUGUST 25, 2023

That’s why it’s essential for teams to choose the right architecture for the storage layer of their data stack. But, the options for data storage are evolving quickly. So let’s get to the bottom of the big question: what kind of data storage layer will provide the strongest foundation for your data platform?

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Knowledge Hut

MARCH 7, 2024

For you to make decisions and see how they will affect this grouping, businesses utilize the best big data analytics tools that can be used to forecast and determine behavior on a huge scale. You can opt for the Big Data Analytics Training to learn more about big data analytics and how you can utilize it.

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Knowledge Hut

APRIL 25, 2024

Compute: Through the method of computing, or data processing, is an important aspect of Information Technology. It helps in storing the data in the CPU. Data Storage: The place where the information is stated somewhere safe without directly being processed. It is looked after by the Database Management System (DBMS).

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Technology Recruitment Media Cloud Computing 52

Cloudera

SEPTEMBER 15, 2022

Today’s platform owners, business owners, data developers, analysts, and engineers create new apps on the Cloudera Data Platform and they must decide where and how to store that data. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases.

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Knowledge Hut

JANUARY 3, 2024

A linear data structure is one where data items are arranged in a linear fashion. The structure permits single-level data storage because the data elements are stored in a linear fashion. The data can be traversed in one run. A linear data structure does not maximize memory.

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Data Storage Data Systems Data Science 52

Edureka

FEBRUARY 9, 2023

Data engineering is a new and evolving field that will withstand the test of time and computing advances. Certified Azure Data Engineers are frequently hired by businesses to convert unstructured data into useful, structured data that data analysts and data scientists can use.

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Data Engineering Data Engineer Engineering Data Mining 52

Edureka

JANUARY 18, 2024

Data science is the study of data to extract knowledge and insights from structured and unstructured data using scientific methods, processes, and algorithms. Introduction of R as an optional language in data science, highlighting its strengths in statistics and visualization.

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Data Science Deep Learning NoSQL Machine Learning 40

Snowflake

JULY 10, 2023

Historically, organizations have relied heavily on structured tables and semi-structured data like JSON and XML for analytical workloads and applications. “Our team worked on a use case where sensitive data was submitted in PDF format and manually converted into tabular data for analytics.

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Unstructured Data Python Process Scala 40

AltexSoft

JULY 18, 2023

This article will expose Apache Spark architecture, assess its advantages and disadvantages, compare it with other big data technologies, and provide you with the path to learning this impactful instrument. Maintained by the Apache Software Foundation, Apache Spark is an open-source, unified engine designed for large-scale data analytics.

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Big Data Data Process Process Hadoop 52

Knowledge Hut

DECEMBER 26, 2023

After carefully exploring what we mean when we say "big data," the book explores each phase of the big data lifecycle. With Tableau, which focuses on big data visualization , you can create scatter plots, histograms, bar, line, and pie charts. Learn how big data transform banking, law, hospitality, fashion, and science.

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Big Data Data Mining Business Intelligence Machine Learning 75

Edureka

JUNE 1, 2023

What is Data Analytics? Data analytics is the process of converting raw data into actionable insights. It encompasses a variety of tools, technologies, and procedures that utilize data to identify patterns and solve issues. Why is Data Analytics important?

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AWS Data Analytics Cloud Amazon Web Services 52

Rockset

SEPTEMBER 20, 2022

Other companies store all the smart contract data in one table and then use aggregation frameworks to simplify the data storage. Image Source Regardless of the approach, these companies typically expose the data to users by allowing them to write custom SQL queries.

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AltexSoft

MARCH 14, 2023

According to a recent Matillion and IDG Research survey , the average number of data sources per organization is 400. Moreover, over 20 percent of surveyed companies were found to be utilizing 1,000 or more data sources to provide data to analytics systems. Data storage component in a modern data stack.

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IT Data Warehouse Data Governance Data Lake 59

Knowledge Hut

MAY 31, 2023

Business Intelligence is closely knitted to the field of data science since it leverages information acquired through large data sets to deliver insightful reports. Companies utilize different approaches to deal with data in order to extract information from structured, semi-structured, or unstructured data sets.

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Business Intelligence BI Business Analyst Consulting 52

Snowflake

MARCH 30, 2023

Snowflake can also ingest external tables from on-premise s data sources via S3-compliant data storage APIs. Batch/file-based data is modeled into the raw vault table structures as the hub, link, and satellite tables illustrated at the beginning of this post. Enter Snowpark !

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Engineering Raw Data Data Science Scala 83

LinkedIn Engineering

JULY 19, 2023

Open source data lakehouse deployments are built on the foundations of compute engines (like Apache Spark, Trino, Apache Flink), distributed storage (HDFS, cloud blob stores), and metadata catalogs / table formats (like Apache Iceberg, Delta, Hudi, Apache Hive Metastore). The framework itself is extensible to run custom jobs.

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Big Data Data Management Management Metadata 78

AltexSoft

JUNE 7, 2021

Master Nodes control and coordinate two key functions of Hadoop: data storage and parallel processing of data. Worker or Slave Nodes are the majority of nodes used to store data and run computations according to instructions from a master node. Data storage options. Data management and monitoring options.

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Monte Carlo

JANUARY 25, 2023

In this article, we’ll take a closer look at the data storage level of the data stack to determine when to invest in storage and compute tooling, what “build versus buy” really means when it comes to storage and compute, and how our five considerations might impact your decision. Let’s jump in!

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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.

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Data Engineering Data Engineer Engineering Scala 52

ProjectPro

SEPTEMBER 9, 2021

Apache Hive and Apache Spark are the two popular Big Data tools available for complex data processing. To effectively utilize the Big Data tools, it is essential to understand the features and capabilities of the tools. Spark SQL, for instance, enables structured data processing with SQL.

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Hadoop Big Data Tools Java SQL 52

Knowledge Hut

DECEMBER 13, 2023

Hyperlink Infosystem As a trustworthy provider of data science services, Hyperlink InfoSystem enables businesses to develop and carry out well-thought-out big data programs. Micro Focus has rapidly amassed a robust portfolio of Big Data products in just a short amount of time. This tool can process up to 80 terabytes of data.

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Knowledge Hut

JANUARY 18, 2024

4 Purpose Utilize the derived findings and insights to make informed decisions The purpose of AI is to provide software capable enough to reason on the input provided and explain the output 5 Types of Data Different types of data can be used as input for the Data Science lifecycle.

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Data Science Deep Learning Business Analyst Data Mining 98

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. Data Variety Hadoop stores structured, semi-structured and unstructured data.

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Big Data Hadoop AWS Relational Database 52

ProjectPro

JANUARY 25, 2022

Yahoo utilizes Apache Spark's Machine Learning capabilities to customize its news, web pages, and advertising. PySpark SQL and Dataframes A dataframe is a shared collection of organized or semi-structured data in PySpark. With PySparkSQL, we can also use SQL queries to perform data extraction.

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ProjectPro

JANUARY 24, 2023

Furthermore, BigQuery supports machine learning and artificial intelligence, allowing users to use machine learning models to analyze their data. BigQuery Storage BigQuery leverages a columnar storage format to efficiently store and query large amounts of data. Q: Which two services does BigQuery provide?

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Bytes Google Cloud Data Warehouse Datasets 52

Edureka

FEBRUARY 7, 2023

The main advantage of Azure Files over Azure Blobs is that it allows for folder-based data organisation and is SMB compliant, allowing for use as a file share. Storage for Azure VMs is provided by Azure Disks (Virtual Machines). 13) Examine the capabilities of Azure storage explorer. 15) What is Azure table storage, exactly?

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Silectis

JANUARY 3, 2021

Data lakes allow for more flexibility than a more rigid data warehouse. Data Lineage Data lineage describes the origin and changes to data over time Data Management Data management is the practice of collecting, maintaining, and utilizing data securely and effectively.

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Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

JULY 26, 2023

Variety: Variety represents the diverse range of data types and formats encountered in Big Data. Traditional data sources typically involve structured data, such as databases and spreadsheets. Handling this variety of data requires flexible data storage and processing methods.

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Big Data Data Cleanse Retail Healthcare 52

ProjectPro

JANUARY 31, 2022

Snowflake uses a central data repository accessible from all compute nodes in the platform, like shared-disk systems. Snowflake, however, utilizes MPP (massively parallel processing) compute clusters to perform queries. Each node in the cluster keeps a piece of the entire data set locally, like shared-nothing systems.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

AltexSoft

MAY 14, 2021

A growing number of companies now use this data to uncover meaningful insights and improve their decision-making, but they can’t store and process it by the means of traditional data storage and processing units. Key Big Data characteristics. And most of this data has to be handled in real-time or near real-time.

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Big Data Data Analytics IT NoSQL 78

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? This is frequently referred to as a 5 or 7 layer (depending on who you ask) data stack like in the image below.

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ProjectPro

MAY 31, 2021

To create a successful data project, collect and integrate data from as many different sources as possible. Here are some options for collecting data that you can utilize: Connect to an existing database that is already public or access your private database. Here are some good practices for successful Big Data projects.

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