ProjectPro

MAY 31, 2021

Ace your big data interview by adding some unique and exciting Big Data projects to your portfolio. This blog lists over 20 big data projects you can work on to showcase your big data skills and gain hands-on experience in big data tools and technologies. Table of Contents What is a Big Data Project?

Big Data 52

Big Data Coding Project Hadoop 52

AltexSoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

FEBRUARY 8, 2023

Let us dive deeper into this data integration solution by AWS and understand how and why big data professionals leverage it in their data engineering projects. AWS Glue then creates data profiles in the catalog, a repository for all data assets' metadata, including table definitions, locations, and other features.

AWS 98

AWS Scala Metadata Data Lake 98

ProjectPro

OCTOBER 18, 2021

Machine Learning Projects are the key to understanding the real-world implementation of machine learning algorithms in the industry. These machine learning projects for students will also help them understand the applications of machine learning across industries and give them an edge in getting hired at one of the top tech companies.

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

Cloudera

SEPTEMBER 15, 2022

The collection of source data shown on your left is composed of both structured and unstructured data from the organization’s internal and external sources. One of the tenets of a modern data platform is a focus on the entire source data landscape versus the traditional approach of limiting to project-level requirements. .

Data Lake 81

Data Lake Analytics Application Cloud Storage Architecture 81

Knowledge Hut

APRIL 25, 2024

You'll be better able to comprehend the complex ideas in this field if you have a solid understanding of the characteristics of big data in data analytics and a list of essential features for new data platforms. What Are the Different Features of Big Data Analytics? The main features of big data analytics are: 1.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

Knowledge Hut

DECEMBER 22, 2023

Statistics are used by data scientists to collect, assess, analyze, and derive conclusions from data, as well as to apply quantifiable mathematical models to relevant variables. Microsoft Excel An effective Excel spreadsheet will arrange unstructured data into a legible format, making it simpler to glean insights that can be used.

Hadoop 98

Hadoop Deep Learning Data Science Machine Learning 98

Cloudera

OCTOBER 7, 2021

Also included, business and technical metadata, related to both data inputs / data outputs, that enable data discovery and achieving cross-organizational consensus on the definitions of data assets. PII data) of each data product, and the access rights for each different group of data consumers.

Architecture 124

Architecture Metadata Government Kafka 124

Knowledge Hut

APRIL 26, 2024

Let's take a look at all the fuss about data science , its courses, and the path to the future. What is Data Science? In order to discover insights and then analyze multiple structured and unstructured data, Data Science requires the use of different instruments, algorithms and principles.

Data Science 52

Data Science Machine Learning Hadoop Programming Language 52

Cloudera

SEPTEMBER 1, 2020

DDE also makes it much easier for application developers or data workers to self-service and get started with building insight applications or exploration services based on text or other unstructured data (i.e. data best served through Apache Solr). What does DDE entail? Provides perimeter security.

Cloud Storage 68

Cloud Storage Unstructured Data AWS Analytics Application 68

Knowledge Hut

NOVEMBER 7, 2023

With quick access to various technologies through the cloud, you can develop more quickly and create almost anything you can imagine. You can swiftly provision infrastructure services like computation, storage, and databases, as well as machine learning, the internet of things, data lakes and analytics, and much more.

Cloud Computing 98

Cloud Computing Cloud Amazon Web Services Entertainment 98

ProjectPro

FEBRUARY 16, 2023

Category Business Intelligence (BI) Artificial Intelligence (AI) Definition A set of processes, architectures, and technologies that convert raw data into meaningful and useful information for business analysis purposes. Input Data Structured data from various sources, such as databases, spreadsheets, and ERP systems.

Business Intelligence 52

Business Intelligence BI Data Mining Raw Data 52

ProjectPro

AUGUST 16, 2021

All you need to do is highlight different types of machine learning projects on your resume. Table of Contents Machine Learning Projects for Resume - A Must-Have to Get Hired in 2021 Machine Learning Projects for Resume - The Different Types to Have on Your CV 1. Machine Learning Projects on Classification 2.

Machine Learning 40

Machine Learning Coding Project Deep Learning 40

Knowledge Hut

MARCH 15, 2024

5) AZ-204: Microsoft Azure Developer Associate Developers working on cloud projects in all stages—from requirements, definition, and design through development, deployment, and maintenance to performance tuning and monitoring—are an ideal group for this Professional Certificate.

Cloud Computing 52

Cloud Computing Algorithm Certification SQL 52

Knowledge Hut

SEPTEMBER 22, 2023

Is Azure Data Engineer Certification Worth It? In my opinion, Azure Data Engineer Certification is definitely worth it for people who wish to make a career in this field. A profession in Azure data engineering can be satisfying even when it is challenging. How Long Does Microsoft Azure Data Engineer Certification Take?

Certification 52

Certification Data Engineering Data Engineer Engineering 52

DataKitchen

APRIL 13, 2021

Because it is such a new category, both overly narrow and overly broad definitions of DataOps abound. DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. Quilt Data — Versions and deploys data.

Consulting 120

Consulting Machine Learning Data Science Data Pipeline 120

Monte Carlo

AUGUST 31, 2023

Your downstream data consumers including product analysts, marketing leaders, and sales teams rely on data-driven tools like CRMs, CXPs, CMSs, and any other acronym under the sun to do their jobs quickly and effectively. But what happens when the data is wrong? What is Data Quality? It certainly didn’t to us.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Knowledge Hut

DECEMBER 26, 2023

Leveraging Apache technologies like Hadoop, Cassandra, Avro, Pig, Mahout, Oozie, and Hive to encapsulate, split, and isolate Big Data and virtualize Big Data servers. Examining business cases, preparing, extracting, transforming, analyzing, and displaying data are steps in the big data analytics lifecycle.

Big Data 75

Big Data Data Mining Business Intelligence Machine Learning 75

Ascend.io

DECEMBER 14, 2022

In the hopes of resolving this issue, ETL tasks that update hundreds or millions of data warehouse tables frequently take place at night. But in a world that favors the here and now, ETL processes lack in the area of providing analysts with new, fresh data. The same principle guides data transformations in the ELT process.

Data Integration 52

Data Integration Raw Data Data Consolidation Data Warehouse 52

ProjectPro

JUNE 9, 2021

As we proceed further into the blog, you will find some statistics on data engineering vs. data science jobs and data engineering vs. data science salary, along with an in-depth comparison between the two roles- data engineer vs. data scientist. vs. What does a Data Engineer do? What is Data Science?

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Knowledge Hut

JUNE 20, 2023

Data Engineer vs Machine Learning Engineer While there are similarities between a data engineer and a machine learning engineer, both play a key role in the technological world. Factors Data Engineer Machine Learning Definition Data engineers create, maintain, and optimize data infrastructure for data.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

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

AUGUST 3, 2022

Data Scientist roles and responsibilities have become increasingly challenging, fun, and worthwhile. . Although the term “Data Science” might imply various things to various individuals, it is essentially the use of data to provide answers to inquiries. What are Data Scientist roles?

Retail 52

Retail Data Science Computer Science Entertainment 52

ProjectPro

JULY 27, 2021

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

JUNE 23, 2023

Application makers apply real-time data analytics to include real-time analytics databases in their products, giving clients quick access to data insights. Real-time data analytics are applied in transportation to improve safety, plan paths, and watch traffic.

Data Analytics 52

Data Analytics IT Transportation Analytics Architecture 52

ProjectPro

MAY 5, 2015

The experts are very knowledgeable on the subject and I feel have a lot of industry experience which definitely helps. I got a lot of examples from their professional experience which definitely helped understand the relevance of the projects in the professional world." Overall, all the concepts are clear and crisp.

Big Data 40

Big Data Project Hadoop Java 40

Knowledge Hut

DECEMBER 26, 2023

The spectrum of sources from which data is collected for the study in Data Science is broad. These data have been accessible to us because of the advanced and latest technologies which are used in the collection of data. Knowledge of Python and data visualization tools are common skills for both.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

ProjectPro

MARCH 17, 2021

What follows is a straightforward and easy-to-understand primer on “Deep Learning” vs “Machine Learning” Table of Contents Deep Learning vs Machine Learning – Understanding the Differences Machine Learning vs Deep Learning – The Definition What is Machine Learning? What is Deep Learning?

Deep Learning 52

Deep Learning Machine Learning Algorithm Datasets 52

ProjectPro

MARCH 16, 2015

Since then, there has been an exponential increase in data which has lead to an expenditure of $1.2 trillion towards healthcare data solutions in the Healthcare industry. McKinsey projects that the use of Big Data in healthcare can reduce the healthcare data management expenses by $300 billion -$500 billion.

Healthcare 40

Healthcare Big Data Project Hospitality 40

AltexSoft

MARCH 30, 2023

Shell, Adobe, Burberry, Columbia, Bayer — you definitely know the names. The answer is simple: They use the same technology to make the most of data. Along with thousands of other data-driven organizations from different industries, the above-mentioned leaders opted for Databrick to guide strategic business decisions.

Scala 64

Scala Data Lake BI Google Cloud 64

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

Meltano

OCTOBER 5, 2022

To reduce development time and increase data reliability, DataOps engineers automate manual processes, such as data extraction and testing. Managing the production of data pipelines. A DataOps engineer provides organizations with access to structured datasets and analytics they will further analyze and derive insights from.

Engineering 52

Engineering Raw Data Data Pipeline ETL Tools 52

AltexSoft

JULY 29, 2022

a runtime environment (sandbox) for classic business intelligence (BI), advanced analysis of large volumes of data, predictive maintenance , and data discovery and exploration; a store for raw data; a tool for large-scale data integration ; and. a suitable technology to implement data lake architecture.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Knowledge Hut

NOVEMBER 20, 2023

AI vs Automation [Head-to-Head Comparison] Parameters Artificial Intelligence Automation Definition AI is a collection of technologies that collectively allow machines to act like humans by mimicking their intelligence. They can also work with unstructured data (like emails, feedback, webpages, images, videos, etc.)

Manufacturing 52

Manufacturing Pharmaceutical Healthcare Finance 52

ProjectPro

NOVEMBER 30, 2021

If you are into Data Science or Big Data, you must be familiar with an ETL pipeline. This guide provides definitions, a step-by-step tutorial, and a few best practices to help you understand ETL pipelines and how they differ from data pipelines. It is the most feasible option when the data size is huge.

Process 52

Process Data Pipeline Data Warehouse AWS 52

ProjectPro

NOVEMBER 30, 2021

Data Science is a technique that isn’t specific to a particular domain; we can use it to solve any discipline’s problem. Get Closer To Your Dream of Becoming a Data Scientist with 70+ Solved End-to-End ML Projects What is Data Mining? Data Mining isn’t something new.

Data Mining 52

Data Mining Machine Learning Data Science Algorithm 52

Cloudera

AUGUST 30, 2018

Consider the following practices that, until recently, were relegated to the R&D department: Data-driven decision making – the collection and analysis of data to guide decisions that improve success. Will I end up with a huge bill as projects scale and ultimately require continuously running cloud instances?

Unstructured Data 40

Unstructured Data Machine Learning Data Warehouse BI 40