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

DareData

MARCH 5, 2024

In this blog post, we'll delve into some of our project portfolio in the Generative AI space and understand how we are deploying GenAI at our customers. This project serves as a bridge between two historically distinct realms: coding and sales.

Database-centric 52

Database-centric Telecommunication SQL Unstructured Data 52

Knowledge Hut

JUNE 23, 2023

You can simultaneously work on your skills, knowledge, and experience and launch your career in data engineering. Soft Skills You should have the right verbal and written communication skills required for a data engineer. Soft Skills You should have the right verbal and written communication skills required for a data engineer.

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 52

Knowledge Hut

APRIL 3, 2023

In addition to technical skills, the roadmap highlights the importance of understanding DevOps practices, such as containerization, continuous integration, and deployment (CI/CD), and infrastructure as code. This includes concepts such as authentication, authorization, encryption, and secure coding practices.

Programming Language 52

Programming Language Computer Science Portfolio PostgreSQL 52

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

Knowledge Hut

NOVEMBER 28, 2023

Data engineers design, manage, test, maintain, store, and work on the data infrastructure that allows easy access to structured and unstructured data. Data engineers need to work with large amounts of data and maintain the architectures used in various data science projects.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Knowledge Hut

MARCH 19, 2024

RDS should be utilized with NoSQL databases like Amazon OpenSearch Service (for text and unstructured data) and DynamoDB (for low-latency/high-traffic use cases). Challenge Sunsetting technology put this project on a surged timeline. It is the perfect fit for complex daily database requirements that are OLTP/transactional.

AWS 52

AWS Amazon Web Services Hospitality Cloud Computing 52

Snowflake

DECEMBER 14, 2023

Whereas the existing portfolio of AI tools had targeted the more technically minded like data scientists and engineers, new tools like ChatGPT handed the keys to the kingdom to anyone who could type a question. In fact, it was only one employee—an intern learning to code side-by-side with her AI co-pilot.

Pharmaceutical 100

Pharmaceutical Food Government Transportation 100

Knowledge Hut

JANUARY 24, 2024

This blog offers an exclusive glimpse into the daily rituals, challenges, and moments of triumph that punctuate the professional journey of a data scientist. In their quest for knowledge, data scientists meticulously identify pertinent questions that require answers and source the relevant data for analysis.

Database-centric 52

Database-centric Data Science Machine Learning Datasets 52

Knowledge Hut

MARCH 20, 2024

Usually working in groups, software engineers collaborate with designers, project managers, and quality assurance specialists. They write code to develop frameworks and tools for automated testing, which speeds up the testing procedure and raises the caliber of software. Writes code to build tools and frameworks for automated testing.

Software Engineer 52

Software Engineer Software Engineering Engineering Java 52

ProjectPro

JUNE 24, 2021

Table of Contents Skills Required for Data Analytics Jobs Why Should Students Work on Big Data Analytics Projects ? 10+ Real-Time Azure Project Ideas for Beginners to Practice Access Job Recommendation System Project with Source Code Why Should Students Work on Big Data Analytics Projects ?

Data Analytics 40

Data Analytics Project Insurance Hadoop 40

Knowledge Hut

NOVEMBER 16, 2023

More and more companies are focusing on hiring data scientists to help them unlock the true potential of their businesses and channelize maximum profits. A data scientist is a person expert in analytics, especially gathering and evaluating large chunks of structured and unstructured data to find trends and proper data management.

IT 52

IT Software Engineer Software Engineering Cloud Computing 52

Knowledge Hut

DECEMBER 27, 2023

In this course, you learn about leading a team, engagement of people, project management, strategic planning and much more. It is a two years program best suited for candidates interested in finance project planning, economic analysis, and corporate audit planning. However, a Portfolio Manager can be active or passive.

Banking 52

Banking Recruitment Finance Portfolio 52

ProjectPro

JANUARY 19, 2022

Azure Data Engineers Jobs - The Demand Azure Data Engineer Salary Azure Data Engineer Skills What does an Azure Data Engineer Do? Data is an organization's most valuable asset, so ensuring it can be accessed quickly and securely should be a primary concern. The use of data has risen significantly in recent years.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

ProjectPro

SEPTEMBER 9, 2021

Explore SQL Database Projects to Add them to Your Data Engineer Resume. Hive , for instance, does not support sub-queries and unstructured data. The tool also has acceptable latency for interactive data browsing, and it causes adverse implications on the overall performance.

Hadoop 52

Hadoop Big Data Tools Java SQL 52

Knowledge Hut

NOVEMBER 7, 2023

Because this type of setting is not cost-effective, it will put a burden on a project's budget and deadline. Every day, enormous amounts of data are collected from business endpoints, cloud apps, and the people who engage with them. A full stack developer must be continually informed of new coding languages and train in them.

Cloud Computing 98

Cloud Computing Cloud Amazon Web Services Entertainment 98

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. However, it is not straightforward to create data pipelines.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Knowledge Hut

MARCH 26, 2024

The solutions architect must make sure that the needs of all parties are taken into account and factored into the project's scope because most projects involve both technical and non-technical stakeholders. This provides opportunities for diverse and challenging projects, even for entry-level AWS solutions architect jobs.

Amazon Web Services 52

Amazon Web Services Google Cloud Computer Science AWS 52

Knowledge Hut

FEBRUARY 7, 2023

A data science platform is software that includes a variety of technologies for machine learning, data science, and other advanced analytics projects. Typically, data science projects involve using an abundance of ls (eg. Lots of packages and environments can complicate simple stuff sometimes.

Data Science 52

Data Science Google Cloud AWS Programming Language 52

ProjectPro

MAY 5, 2015

I got a lot of examples from their professional experience which definitely helped understand the relevance of the projects in the professional world." I was fortunate enough to get the chance to work on a Big Data project which involved deploying a Hadoop cluster and this helped me immensely. would love to hear from you.

Big Data 40

Big Data Project Hadoop Java 40

ProjectPro

SEPTEMBER 26, 2021

Automated tools are developed as part of the Big Data technology to handle the massive volumes of varied data sets. Big Data Engineers are professionals who handle large volumes of structured and unstructured data effectively. Big Data technologies are now being used in multiple industries and business sectors.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 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

ProjectPro

SEPTEMBER 16, 2021

NoSQL databases are the new-age solutions to distributed unstructured data storage and processing. The speed, scalability, and fail-over safety offered by NoSQL databases are needed in the current times in the wake of Big Data Analytics and Data Science technologies. HBase vs. Cassandra - What’s the Difference?

NoSQL 52

NoSQL Database Hadoop Big Data 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

ProjectPro

NOVEMBER 30, 2021

Corrupted Text : When we usually extract data stored in the upstream systems via APIs or scraping, the data may look messy. For example, address data may have misspelled street names, incorrect zip codes, etc., or mobile numbers may have special symbols and country codes appended before them.

Process 52

Process Data Pipeline Data Warehouse AWS 52

ProjectPro

JANUARY 24, 2023

Additionally, columnar storage allows BigQuery to compress data more effectively, which helps to reduce storage costs. BigQuery enables users to store data in tables, allowing them to quickly and easily access their data. It supports structured and unstructured data, allowing users to work with various formats.

Bytes 52

Bytes Google Cloud Data Warehouse Datasets 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

Cloudera

SEPTEMBER 17, 2018

You can also easily preview and sample the data to validate you have found the relevant assets to work with. Often SQL users step away or get interrupted and need to revisit the coding at a later time. Hue, in addition, persists your work, expediting SQL users to start new projects. Query Design. Optimization.

Data Warehouse 53

Data Warehouse SQL Portfolio MySQL 53

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 allows us to store data that we never stored before.

Hadoop 52

Hadoop Big Data Data Analytics Banking 52

AltexSoft

DECEMBER 15, 2021

AutoML objectives and benefits overlap with those of MLOps — a broader discipline with focus not only on automation but also on cross-functional collaboration within machine learning projects. Things changed with employing the Squark platform that focuses on low-code AutoML solutions. Algorithm selection.

Machine Learning 59

Machine Learning Deep Learning Algorithm Telecommunication 59

ProjectPro

SEPTEMBER 14, 2016

How much java coding is involved in hadoop development job ? The better a hadoop developer knows the data, the better they know what kind of results are possible with that amount of data. Concisely, a hadoop developer plays with the data, transforms it, decodes it and ensure that it is not destroyed.

Hadoop 40

Hadoop Unstructured Data Java Big Data 40

ProjectPro

MAY 26, 2015

The webinar discusses about the working of beacon technology (Beaconstac) and the production beacon analytics system Morpheus at MobStac that leverages Hadoop for analysing huge amounts of unstructured data generated from beacons (IoT).Beacons “–says, Fabrizio Biscotti, research director at Gartner.

Hadoop 52

Hadoop Unstructured Data Big Data Retail 52

ProjectPro

MARCH 17, 2021

Deep learning models usually perform Classification tasks directly from sound, text, or images (unstructured data). Get FREE Access to Machine Learning and Data Science Example Codes Deep Learning vs Machine Learning – Which one to choose based on data? Build a Job-Winning Data Science Portfolio.

Deep Learning 52

Deep Learning Machine Learning Algorithm Datasets 52

ProjectPro

SEPTEMBER 30, 2014

While the initial era of ETL ignited enough sparks and got everyone to sit up, take notice and applaud its capabilities, its usability in the era of Big Data is increasingly coming under the scanner as the CIOs start taking note of its limitations.

Hadoop 52

Hadoop Unstructured Data ETL Tools ETL System 52

ProjectPro

DECEMBER 7, 2016

Hive and HBase are both data stores for storing unstructured data. HBase is a NoSQL database used for real-time data streaming whereas Hive is not ideally a database but a MapReduce based SQL engine that runs on top of hadoop. Explore SQL Database Projects to Add them to Your Data Engineer Resume.

Technology 40

Technology NoSQL Hadoop Data Mining 40

ProjectPro

JULY 22, 2016

Data warehouses do a good job for what they are meant to do, but with disparate data sources and different data types like transaction logs, social media data, tweets, user reviews, and clickstream data –Data Lakes fulfil a critical need.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

ProjectPro

AUGUST 26, 2015

Here’s a look at important milestones, tracking the evolutionary progress on how data has been collected, stored, managed and analysed- 1926 – Nikola Tesla predicted that humans will be able to access and analyse huge amounts of data in the future by using a pocket friendly device. 1937 - Franklin D. Truskowski.

Big Data 40

Big Data Unstructured Data Hadoop NoSQL 40