Knowledge Hut

JANUARY 11, 2024

I’ve observed that ever since data science techniques and approaches, including data science for finance, have made their way into different industrial domains, the growth has been tremendous. That is why companies are introducing data science into their operations and looking for people who can do efficient data analysis.

Finance 93

Finance Data Science Programming Language Machine Learning 93

Knowledge Hut

FEBRUARY 28, 2024

In this blog, we will explore the future of big data in business, its applications, and the technologies that will drive its evolution. What is Big Data? Big data refers to large amounts of data. The differentiation between data and big data becomes clear once we look at the methods of analyzing them.

Big Data 52

Big Data Cloud Storage Healthcare SQL 52

AltexSoft

JUNE 26, 2023

The ultimate goal of data integration is to gather all valuable information in one place, ensuring its integrity , quality, accessibility throughout the company, and readiness for BI, statistical data analysis, or machine learning. Key differences between structured, semi-structured, and unstructured data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Silectis

JANUARY 3, 2021

BI (Business Intelligence) Strategies and systems used by enterprises to conduct data analysis and make pertinent business decisions. Big Data Large volumes of structured or unstructured data. Data Visualization Graphic representation of a set or sets of data. Database A collection of structured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

JULY 24, 2023

According to recent studies, the global database market will grow from USD 63.4 SQL is a powerful tool for managing and manipulating relational databases, and it continues to be widely used in the industry today. One of its most significant benefits is its ability to quickly process a vast amount of data.

Database 52

Database SQL Process NoSQL 52

Knowledge Hut

DECEMBER 26, 2023

Analyzing and organizing raw data Raw data is unstructured data consisting of texts, images, audio, and videos such as PDFs and voice transcripts. The job of a data engineer is to develop models using machine learning to scan, label and organize this unstructured data.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Knowledge Hut

SEPTEMBER 22, 2023

Data Engineers On-site and cloud data platform technologies are configured and provisioned by data engineers. They control and protect the flow of both organised and unstructured data coming from various sources. Data Scientists To extract value from data, data scientists undertake advanced analysis.

Certification 52

Certification Data Engineering Data Engineer Engineering 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 AWS Relational Database 52

AltexSoft

AUGUST 29, 2023

Data sources In a data lake architecture, the data journey starts at the source. Data sources can be broadly classified into three categories. Structured data sources. These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

SEPTEMBER 29, 2023

The Azure Data Engineer Certification test evaluates one's capacity for organizing and putting into practice data processing, security, and storage, as well as their capacity for keeping track of and maximizing data processing and storage. They control and safeguard the flow of organized and unstructured data from many sources.

Certification 52

Certification Data Engineering Data Engineer Engineering 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? ETL is central to getting your data where you need it.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 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

phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. It follows a predefined schema and enforces data normalization and standardization.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

AltexSoft

FEBRUARY 11, 2023

The former uses data to generate insights and help businesses make better decisions, while the latter designs data frameworks, flows, standards, and policies that facilitate effective data analysis. But first, all candidates must be accredited by Arcitura as Big Data professionals.

Data Architect 87

Data Architect Certification Generalist Big Data 87

ProjectPro

JANUARY 27, 2023

ETL is essential in the healthcare sector to export data from one source, often an EHR, and transform it into a format compatible with the target database's structure, where the data will be stored, either for future reference or delivered in a presentation-ready format.

BI 52

BI ETL Tools Retail Healthcare 52

AltexSoft

MAY 14, 2021

And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. This data isn’t just about structured data that resides within relational databases as rows and columns. Data analysis.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Knowledge Hut

JANUARY 30, 2024

Structured Data: Structured data sources, such as databases and spreadsheets, often require extraction to consolidate, transform, and make them suitable for analysis. Unstructured Data: Unstructured data, like free-form text, can be challenging to work with but holds valuable insights.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Knowledge Hut

SEPTEMBER 26, 2023

Supports Structured and Unstructured Data: One of Azure Synapse's standout features is its versatility in handling a wide array of data types. Whether your data is structured, like traditional relational databases, or unstructured, such as textual data, images, or log files, Azure Synapse can manage it effectively.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

AltexSoft

JUNE 7, 2021

MapReduce performs batch processing only and doesn’t fit time-sensitive data or real-time analytics jobs. Data engineers who previously worked only with relational database management systems and SQL queries need training to take advantage of Hadoop. Cassandra excels at streaming data analysis.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

U-Next

AUGUST 3, 2022

A high-ranking expert is known as a “Data Scientist” who works with big data and has the mathematics, economic, technical, analytic, and technological abilities necessary to cleanse, analyse and evaluate organised and unstructured data to help organisations make more informed decisions.

Retail 52

Retail Data Science Computer Science Entertainment 52

Edureka

FEBRUARY 9, 2023

This includes practical knowledge of data ingestion methods like incremental loading and bulk loading, as well as experience with data transformation using Azure Data Factory. It’s a versatile language that is well-suited to a wide range of data engineering tasks, and its use in Azure is widespread.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

U-Next

SEPTEMBER 23, 2022

Previously, organizations dealt with static, centrally stored data collected from numerous sources, but with the advent of the web and cloud services, cloud computing is fast supplanting the traditional in-house system as a dependable, scalable, and cost-effective IT solution. Stage 1: presenting a Big Data framework and platform. .

Big Data Ecosystem 40

Big Data Ecosystem Big Data Healthcare Data Lake 40

ProjectPro

OCTOBER 28, 2015

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

U-Next

SEPTEMBER 29, 2022

Are you looking for fruitful results and actionable insights from your data assets in order to improve the quality and rationality of your business decisions with data-driven decisions? Embrace the changes dictated by the valuable insights from the correct data analysis if you want to make your business a purely data-driven entity. .

Management 52

Management Unstructured Data Data Government 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

DECEMBER 17, 2021

Industry experts at ProjectPro say that although both have been developed for the same task, i.e., data storage, they vary significantly in terms of the audience they cater to. NoSQL databases are designed to store unstructured data like graphs, documents, etc., whereas SQL databases deal with structured data in tables.

Data Science 52

Data Science SQL NoSQL Programming Language 52

U-Next

OCTOBER 27, 2022

Using Amazon RDS, you can manage relational databases. You don’t have to worry about patching, taking a backup, or upgrading data. The company provides structured data management services exclusively. Unstructured data can be stored in DynamoDB using NoSQL technology.

AWS 40

AWS Amazon Web Services Cloud Computing Cloud 40

AltexSoft

AUGUST 4, 2021

Modern cloud warehouses make it possible to store data in its raw formats similarly to data lakes. A data mart is a subject-oriented relational database commonly containing a subset of DW data that is specific for a particular business department of an enterprise, e.g., a marketing department.

Data Lake 64

Data Lake Data Warehouse ETL Tools Telecommunication 64

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. Visualizing Wikipedia Trends Big Data Project with Source Code.

Big Data 52

Big Data Coding Project Hadoop 52

AltexSoft

NOVEMBER 10, 2021

Prior to the recent advances in data management technologies, there were two main types of data stores companies could make use of, namely data warehouses and data lakes. Data warehouse. Traditional data warehouse platform architecture. websites, etc.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

ProjectPro

AUGUST 11, 2021

Data Lake vs Data Warehouse - The Differences Before we closely analyse some of the key differences between a data lake and a data warehouse, it is important to have an in depth understanding of what a data warehouse and data lake is. Data Lake vs Data Warehouse - The Introduction What is a Data warehouse?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

ProjectPro

DECEMBER 7, 2021

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. Step 2- Internal Data transformation at LakeHouse.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

AUGUST 26, 2015

1997 -The term “BIG DATA” was used for the first time- A paper on Visualization published by David Ellsworth and Michael Cox of NASA’s Ames Research Centre mentioned about the challenges in working with large unstructured data sets with the existing computing systems. Truskowski. 10 21 i.e. 4.4

Big Data 40

Big Data Unstructured Data Hadoop NoSQL 40

ProjectPro

FEBRUARY 21, 2023

Due to the enormous amount of data being generated and used in recent years, there is a high demand for data professionals, such as data engineers, who can perform tasks such as data management, data analysis, data preparation, etc. The rest of the exam details are the same as the DP-900 exam.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

ProjectPro

JULY 13, 2015

Apache Hadoop is the framework of choice for JPMorgan - not only to support the exponentially growing data size but more importantly for the fast processing of complex unstructured data. JP Morgan has massive amounts of data on what its customers spend and earn.

Hadoop 52

Hadoop Big Data Data Analytics Banking 52

ProjectPro

NOVEMBER 14, 2015

These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis. These Apache Spark projects are mostly into link prediction, cloud hosting, data analysis, and speech analysis. Data Integration 3.Scalability Specialized Data Analytics 7.Streaming

Hadoop 52

Hadoop Project Big Data Healthcare 52

AltexSoft

JULY 29, 2022

It relieves the MapReduce engine of scheduling tasks and decouples data processing from resource management. The most common language for data analysis is SQL but barebone Hadoop doesn’t support it. MongoDB: an NoSQL database with additional features. How YARN master-slave architecture works.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59