U-Next

MARCH 1, 2023

They are also responsible for ensuring that the data is clean and organized, as well as making sure that it’s easily accessible to other departments within the company. They often work closely with database administrators to ensure they have access to all of the tools and resources needed to meet their goals.

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

Towards Data Science

DECEMBER 4, 2023

We’ll build a data architecture to support our racing team starting from the three canonical layers : Data Lake, Data Warehouse, and Data Mart. Data Lake A data lake would serve as a repository for raw and unstructured data generated from various sources within the Formula 1 ecosystem: telemetry data from the cars (e.g.

Data Engineering 88

Data Engineering Data Engineer Engineering Data Lake 88

Monte Carlo

FEBRUARY 15, 2023

This article will define in simple terms what a data warehouse is, how it’s different from a database, fundamentals of how they work, and an overview of today’s most popular data warehouses. What is a data warehouse? Let’s imagine a scenario where you’re collecting orders information.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Grouparoo

JANUARY 11, 2022

When it comes to storing large volumes of data, a simple database will be impractical due to the processing and throughput inefficiencies that emerge when managing and accessing big data. This article looks at the options available for storing and processing big data, which is too large for conventional databases to handle.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

U-Next

SEPTEMBER 7, 2022

A firm can benefit immensely from maintaining accurate and clean employee data, as it is still a difficult task. . Access to employee data and information is essential for efficient staff management. It includes every piece of vital data about an employee on their profiles. . Improved Data Security and Sharing.

Data Management 52

Data Management Management Electronics Unstructured Data 52

Knowledge Hut

JULY 26, 2023

Veracity meaning in big data is the degree of accuracy and trustworthiness of data, which plays a pivotal role in deriving meaningful insights and making informed decisions. This blog will delve into the importance of veracity in Big Data, exploring why accuracy matters and how it impacts decision-making processes.

Big Data 52

Big Data Data Cleanse Retail Healthcare 52

AltexSoft

OCTOBER 18, 2022

Medical Data: What to Consider When Working with Healthcare Information. The main problem with healthcare data is its sensitivity. It contains confidential information which is protected by the Health Insurance Portability and Accountability (HIPAA) act and cannot be used without special consent. Medical data labeling.

Medical 52

Medical Datasets Machine Learning Hospitality 52

Knowledge Hut

MARCH 27, 2024

What Is Big Data Analytics? An organization can make informed decisions based on a big data analytics platform, which works by uncovering patterns, correlations, customer preferences and market trends hidden in the data. Some open-source technology for big data analytics are : Hadoop. Apache Spark. Apache Storm.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

Knowledge Hut

JANUARY 30, 2024

Data extraction is the vital process of retrieving raw data from diverse sources, such as databases, Excel spreadsheets, SaaS platforms, or web scraping efforts. This data can be structured, semi-structured, or entirely unstructured, making it a versatile tool for collecting information from various origins.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Knowledge Hut

DECEMBER 26, 2023

According to the Cybercrime Magazine, the global data storage is projected to be 200+ zettabytes (1 zettabyte = 10 12 gigabytes) by 2025, including the data stored on the cloud, personal devices, and public and private IT infrastructures. They are in charge of the development, deployment, and maintenance of BI interfaces.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

Knowledge Hut

JULY 28, 2023

Data Types and Dimensionality ML algorithms work well with structured and tabular data, where the number of features is relatively small. DL models excel at handling unstructured data such as images, audio, and text, where the data has a large number of features or high dimensionality. When to Use Deep Learning 1.

Deep Learning 52

Deep Learning Machine Learning Unstructured Data Algorithm 52

U-Next

SEPTEMBER 29, 2022

What Is a Data-Driven Culture? . Data on a daily basis surround us. As data becomes more accessible, companies are leveraging it to grow and make an impact. The importance of data today cannot be overstated. Having a data-driven culture is essential for organizations’ survival and growth. .

Management 52

Management Unstructured Data Data Government 52

ProjectPro

JANUARY 27, 2023

However, the vast volume of data will overwhelm you if you start looking at historical trends. The time-consuming method of data collection and transformation can be eliminated using ETL. You can analyze and optimize your investment strategy using high-quality structured data.

BI 52

BI ETL Tools Retail Healthcare 52

Monte Carlo

FEBRUARY 21, 2023

A data fabric isn’t a standalone technology—it’s a data management architecture that leverages an integrated data layer atop underlying data in order to empower business leaders with real-time analytics and data-driven insights. And this innovation ultimately creates bikes that the competition can only dream of.”

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Monte Carlo

FEBRUARY 21, 2023

A data fabric isn’t a standalone technology—it’s a data management architecture that leverages an integrated data layer atop underlying data in order to empower business leaders with real-time analytics and data-driven insights. And this innovation ultimately creates bikes that the competition can only dream of.”

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

AltexSoft

SEPTEMBER 23, 2021

The larger the company, the more data it has to generate actionable insights. Yet, more than often, businesses can’t make use of their most valuable asset — information. Evidently, common storage solutions fail to provide a unified data view and meet the needs of companies for seamless data flow. Data lake vs data hub.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Edureka

AUGUST 2, 2023

Organisations and businesses are flooded with enormous amounts of data in the digital era. This information is gathered from a variety of sources, including sensor readings, social media engagements, and client transactions. Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly.

Data Process 52

Data Process Process Data Cleanse Data Mining 52

Knowledge Hut

DECEMBER 26, 2023

However, as we progressed, data became complicated, more unstructured, or, in most cases, semi-structured. 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.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Knowledge Hut

FEBRUARY 28, 2024

There is no telling what the future of big data technology holds. Ironically, there is a plethora of information out there, and it can be hard to filter through and understand the potential of Big Data online. What is Big Data? Big data refers to large amounts of data.

Big Data 52

Big Data Cloud Storage Healthcare SQL 52

Knowledge Hut

NOVEMBER 28, 2023

Hence, learning and developing the required data engineer skills set will ensure a better future and can even land you better salaries in good companies anywhere in the world. After all, data engineer skills are required to collect data, transform it appropriately, and make it accessible to data scientists.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Knowledge Hut

JUNE 26, 2023

When screening resumes, most hiring managers prioritize candidates who have actual experience working on data engineering projects. Top Data Engineering Projects with Source Code Data engineers make unprocessed data accessible and functional for other data professionals. Which queries do you have?

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

DareData

JULY 5, 2023

We've seen this happen in dozens of our customers: data lakes serve as catalysts that empower analytical capabilities. If you work at a relatively large company, you've seen this cycle happening many times: Analytics team wants to use unstructured data on their models or analysis. And what is the reason for that?

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

Knowledge Hut

JANUARY 24, 2024

In today's digital age, where information permeates every corner of our lives, the role of a data scientist bears a striking resemblance to that of a modern-day explorer. What Does a Data Scientist Do Data scientists are highly skilled professionals specializing in the art of extracting valuable insights from data.

Database-centric 52

Database-centric Data Science Machine Learning Datasets 52

AltexSoft

FEBRUARY 11, 2023

What’s more, investing in data products, as well as in AI and machine learning was clearly indicated as a priority. This suggests that today, there are many companies that face the need to make their data easily accessible, cleaned up, and regularly updated. Feel free to enjoy it.

Data Architect 87

Data Architect Certification Generalist Big Data 87

ProjectPro

JANUARY 31, 2023

If you're looking to break into the exciting field of big data or advance your big data career, being well-prepared for big data interview questions is essential. Get ready to expand your knowledge and take your big data career to the next level! Everything is about data these days.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Knowledge Hut

JUNE 23, 2023

Real-time data analytics is quickly analyzing data to provide actionable insights for enterprises. Real-time analytics analyses the input using machine learning algorithms and other automated technologies to convert an incoming data stream into usable information. Who Uses Real-time Data Analytics?

Data Analytics 52

Data Analytics IT Transportation Analytics Architecture 52

Knowledge Hut

JANUARY 19, 2024

With businesses relying heavily on data, the demand for skilled data scientists has skyrocketed. In data science, we use various tools, processes, and algorithms to extract insights from structured and unstructured data. Recent reports highlight a significant increase in demand for data scientists, rising by 27.9%

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

Knowledge Hut

JUNE 20, 2023

Therefore, keeping up with the latest trends and frameworks and taking online courses like Data Science course review is important. Let's find out the differences between a data scientist and a machine learning engineer below to make an informative decision. Assemble data for predictive and prescriptive modeling.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Knowledge Hut

DECEMBER 26, 2023

Each chapter is set up so that you can easily dip in and out and follows a similar format to help you find the information you need. Find out what information was used, what issue it resolved, and the procedures put in place to make it work for each company profiled.

Big Data 75

Big Data Data Mining Business Intelligence Machine Learning 75

AltexSoft

MAY 27, 2022

The tool processes both structured and unstructured data associated with patients to evaluate the likelihood of their leaving for a home within 24 hours. Data preparation for LOS prediction. As with any ML initiative, everything starts with data. Inpatient data anonymization. MIMIC database. several others.

Hospitality 98

Hospitality Medical Healthcare Algorithm 98

Cloudera

AUGUST 20, 2021

Data Types and Sources: The multitude of data experiences enable efficient processing of different data types, such as structured and unstructured data collected from any potential source. Cloudera has helped organizations across the entire data product development process.

Data Warehouse 96

Data Warehouse Data Architecture Cloud 96

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.

Business Intelligence 52

Business Intelligence BI Business Analyst Consulting 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

APRIL 27, 2023

This phase involves numerous clinical trial systems and largely relies on clinical data management practices to organize information generated during medical research. Obviously, precision medicine requires a large amount of data and is enabled by advanced ML models. The event harmonizer automates data collection and processing.

Data Analytics 52

Data Analytics Pharmaceutical Medical Manufacturing 52

Ascend.io

NOVEMBER 21, 2023

Extract The initial stage of the ELT process is the extraction of data from various source systems. This phase involves collecting raw data from the sources, which can range from structured data in SQL or NoSQL servers, CRM and ERP systems, to unstructured data from text files, emails, and web pages.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

AltexSoft

JUNE 7, 2021

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. But which one of the celebrities should you entrust your information assets to? You don’t need to archive or clean data before loading. How does it work? scalability.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

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