The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Consider whether you need a solution that supports one or multiple data formats.

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The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Consider whether you need a solution that supports one or multiple data formats.

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Data Management Management Data Lake Data Warehouse 52

Knowledge Hut

JANUARY 30, 2024

Goal To extract and transform data from its raw form into a structured format for analysis. To uncover hidden knowledge and meaningful patterns in data for decision-making. Data Source Typically starts with unprocessed or poorly structured data sources. Analyzing and deriving valuable insights from data.

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ETL Tools Database-centric Data Mining Data Cleanse 52

Knowledge Hut

DECEMBER 26, 2023

Thus, to build a career in Data Science, you need to be familiar with how the business operates, its business model, strategies, problems, and challenges. Data Science Roles As Data Science is a broad field, you will find multiple different roles with different responsibilities. Data Analyst Scientist.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

DataKitchen

FEBRUARY 27, 2024

This approach allows LLMs to pull in relevant data when needed, enriching the model’s responses more accurately and contextually. Retrieval of Relevant Data: The system searches a vector database to find pertinent information to augment the LLM’s response.

Data Engineering 48

Data Engineering Data Engineer Engineering Unstructured Data 48

Knowledge Hut

MAY 31, 2023

Artificial intelligence (AI) projects are software-based initiatives that utilize machine learning, deep learning, natural language processing, computer vision, and other AI technologies to develop intelligent programs capable of performing various tasks with minimal human intervention.

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Project Healthcare Deep Learning Transportation 96

Knowledge Hut

NOVEMBER 3, 2023

MongoDB is a NoSQL database that’s been making rounds in the data science community. MongoDB’s unique architecture and features have secured it a place uniquely in data scientists’ toolboxes globally. Let us see where MongoDB for Data Science can help you.

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MongoDB Data Science NoSQL ETL Tools 52

Cloudera

JUNE 7, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

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IT Unstructured Data Data Architecture Government 109

Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. A data warehouse implies a certain degree of preprocessing, or at the very least, an organized and well-defined data model.

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Data Lake Data Warehouse Hadoop Raw Data 59

AltexSoft

OCTOBER 25, 2021

Its deep learning natural language processing algorithm is best in class for alleviating clinical documentation burnout, which is one of the main problems of healthcare technology. NLP-powered systems can derive meaning from what’s said or written, with all the complexities and nuances of natural narrative text. Source: Linguamatics.

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Medical Healthcare Process Hospitality 52

Data Engineering Weekly

JUNE 4, 2023

[link] Uber: Spark Analysers: Catching Anti-Patterns In Spark Apps One of the challenges in commoditizing data processing engines like Spark is that it requires an expert user to understand and operate this system. Many of the real-world data, all the way from medical images to astro monitoring, are unstructured data.

Data Engineering 52

Data Engineering Data Engineer Engineering Medical 52

Knowledge Hut

JULY 28, 2023

We will see how the two technologies differ or overlap and will answer the question - What is the difference between machine learning and deep learning? Data Types and Dimensionality ML algorithms work well with structured and tabular data, where the number of features is relatively small.

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ProjectPro

FEBRUARY 16, 2023

Business Intelligence and Artificial Intelligence are popular technologies that help organizations turn raw data into actionable insights. While both BI and AI provide data-driven insights, they differ in how they help businesses gain a competitive edge in the data-driven marketplace.

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Business Intelligence BI Data Mining Raw Data 52

Monte Carlo

AUGUST 31, 2023

Data is a priority for your CEO, as it often is for digital-first companies, and she is fluent in the latest and greatest business intelligence tools. Your CTO is excited about migrating to the cloud, and constantly sends your team articles highlighting performance measurements against some of the latest technologies.

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Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Knowledge Hut

DECEMBER 29, 2023

The market for analytics is flourishing, as is the usage of the phrase Data Science. Professionals from a variety of disciplines use data in their day-to-day operations and feel the need to understand cutting-edge technology to get maximum insights from the data, therefore contributing to the growth of the organization.

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Data Science Data Mining Deep Learning Programming Language 98

Ascend.io

NOVEMBER 21, 2023

ELT (Extract, Load, Transform) is a data integration technique that collects raw data from multiple sources and directly loads it into the target system, typically a cloud data warehouse. Extract The initial stage of the ELT process is the extraction of data from various source systems.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Cloudera

DECEMBER 11, 2020

Based in Germany, Merck KGaA is one of the leading science and technology companies, operating across healthcare, life science, and performance materials business areas. From advancing gene-editing technologies and discovering unique ways to treat the most challenging diseases, to enabling the intelligence of devices.

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Data Lake Government Data Security Unstructured Data 98

Knowledge Hut

JULY 26, 2023

These datasets typically involve high volume, velocity, variety, and veracity, which are often referred to as the 4 v's of Big Data: Volume: Volume refers to the vast amount of data generated and collected from various sources. Managing and analyzing such large volumes of data requires specialized tools and technologies.

Big Data 52

Big Data Data Cleanse Retail Healthcare 52

Knowledge Hut

NOVEMBER 28, 2023

Then the data is entered into the system, and the management stage begins. The data goes through various stages, such as cleansing, processing, warehousing, and some other processes, before the data scientists start analyzing the data they have garnered. How Much Can You Make as a Data Scientist?

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Data Science Telecommunication Recruitment Finance 52

Data Engineering Podcast

JUNE 17, 2021

Summary Working with unstructured data has typically been a motivation for a data lake. Kirk Marple has spent years working with data systems and the media industry, which inspired him to build a platform for automatically organizing your unstructured assets to make them more valuable.

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Unstructured Data Data Warehouse Metadata Media 100

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? In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline.

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Data Pipeline Architecture Kafka AWS 52

Knowledge Hut

JUNE 19, 2023

Businesses use various data visualization techniques to present information from structured, semi-structured, or unstructured data collections. Adapting to business intelligence skills is necessary to survive in the rapidly growing technology industry.

Business Intelligence 52

Business Intelligence BI Programming Language Recruitment 52

Rockset

JULY 29, 2022

This fast, serverless, highly scalable, and cost-effective multi-cloud data warehouse has built-in machine learning, business intelligence, and geospatial analysis capabilities for querying massive amounts of structured and semi-structured data. So, it’s not real-time data. Pricing starts at $0.25

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Data Analytics Data Warehouse Datasets Google Cloud 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. Paving the way for creating intelligent systems.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

Ascend.io

AUGUST 31, 2023

Modern Cloud Data Platforms The native capabilities of the cloud providers have been joined by third-party services to offload that data into separate less costly systems that are optimized for analysis of that data. Transform before Load: The ETL process conforms data to the static, predefined warehouse schema.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

ProjectPro

SEPTEMBER 30, 2014

To understand the significance of big data and Hadoop for ETL professionals read this article to endorse the awareness on why is this the best time to pursue a career in big data Hadoop for all data warehousing and ETL professionals. As things stand currently, both the technologies are here to stay in the near future.

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Hadoop Unstructured Data ETL Tools ETL System 52

ProjectPro

JULY 22, 2016

The desire to save every bit and byte of data for future use, to make data-driven decisions is the key to staying ahead in the competitive world of business operations. All this is possible due to the low cost storage systems like Hadoop and Amazon S3.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

ProjectPro

OCTOBER 15, 2014

Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Hadoop technology is the buzz word these days but most of the IT professionals still are not aware of the key components that comprise the Hadoop Ecosystem. Pig supports Avro file format.

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Hadoop Unstructured Data Java SQL 52

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.

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Hadoop Big Data Data Analytics Banking 52

ProjectPro

OCTOBER 18, 2021

Recommender System Projects Have you ever seen movies or web series on online streaming platforms? They have a well-researched collection of data such as ratings, reviews, timestamps, price, category information, customer likes, and dislikes. It contains all the attributes you need to build your stock price prediction system.

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

ProjectPro

SEPTEMBER 26, 2014

The toughest challenges in business intelligence today can be addressed by Hadoop through multi-structured data and advanced big data analytics. Big data technologies like Hadoop have become a complement to various conventional BI products and services. Big data, multi-structured data, and advanced analytics.

Business Intelligence 40

Business Intelligence Hadoop BI Relational Database 40

ProjectPro

NOVEMBER 14, 2015

As we step into the latter half of the present decade, we can’t help but notice the way Big Data has entered all crucial technology-powered domains such as banking and financial services, telecom, manufacturing, information technology, operations, and logistics. Data Integration 3.Scalability Scalability 4.Link

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Hadoop Project Big Data Healthcare 52

ProjectPro

JUNE 6, 2015

How can business intelligence scale and analyse the growing data heap? Business Intelligence (BI) combines human knowledge, technologies like distributed computing, and Artificial Intelligence, and big data analytics to augment business decisions for driving enterprise’s success. In BI we just consider structured data.

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Business Intelligence Big Data BI Hadoop 40

ProjectPro

SEPTEMBER 11, 2015

Big Data and Hadoop are moving out of its experimental stage and Hadoop is continuously maturing after having completed 10 years. Learning Hadoop will ensure that your base in the field of Big Data is successfully created and will allow you to move to other big data technologies as per the requirements of your industry.

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Hadoop Java BI Big Data 52

ProjectPro

AUGUST 6, 2015

Let’s take a look at how Amazon uses Big Data- Amazon has approximately 1 million hadoop clusters to support their risk management, affiliate network, website updates, machine learning systems and more. Leveraging analytics from the data, it helps the coach create efficient plays. ” Interesting?

Big Data 52

Big Data Hadoop Insurance Media 52

AltexSoft

JULY 27, 2021

You’ll learn about the types of recommender systems, their differences, strengths, weaknesses, and real-life examples. Personalization and recommender systems in a nutshell. Primarily developed to help users deal with a large range of choices they encounter, recommender systems come into play. Amazon, Booking.com) and.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76

Precisely

SEPTEMBER 6, 2023

To truly succeed in an increasingly data-driven world, organizations need data governance. Data governance is the formal orchestration of people, processes, and technology to enable an organization to leverage data as an enterprise asset. The need for scalable data governance frameworks is growing.

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