Snowflake

JULY 13, 2023

Snowflake is democratizing access to data and intelligence with AI and large language models (LLMs). Snowflake is democratizing access to data and intelligence with AI and large language models (LLMs). More customers are using native applications to power modern customer experiences. Watch the session.

Entertainment 58

Entertainment Retail Manufacturing Media 58

ProjectPro

SEPTEMBER 9, 2021

Hive uses HQL, while Spark uses SQL as the language for querying the data. Access rights is another difference between the two tools with Hive offering access rights and grouping the users as per their roles. Hive , for instance, does not support sub-queries and unstructured data.

Hadoop 52

Hadoop Big Data Tools Java SQL 52

Knowledge Hut

DECEMBER 27, 2023

Apart from all the business knowledge, BBA helps students to build good communication and enhances their confidence. The Program broadly covers a three-tiered approach, building achievement motivation and sharpening entrepreneurial traits and skills. The Portfolio Manager comes with an investment strategy and manages daily trading.

Banking 52

Banking Recruitment Finance Portfolio 52

Cloudera

AUGUST 20, 2021

Legal and Regulatory Requirements: CDP delivers data products to address complex and continuously evolving legal and regulatory requirements by offering a programmatic way to dynamically manage data permissions at a granular level by type of data asset and for different roles / users interacting with and manipulating those data assets. .

Data Warehouse 96

Data Warehouse Data Architecture Cloud 96

ProjectPro

JANUARY 19, 2022

Read this blog till the end to learn more about the roles and responsibilities, necessary skillsets, average salaries, and various important certifications that will help you build a successful career as an Azure Data Engineer. The big data industry is flourishing, particularly in light of the pandemic's rapid digitalization.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Knowledge Hut

JANUARY 24, 2024

In their quest for knowledge, data scientists meticulously identify pertinent questions that require answers and source the relevant data for analysis. Beyond their analytical prowess, they possess the ability to uncover, refine, and present data effectively. Optimizing resource utilization is crucial.

Database-centric 52

Database-centric Data Science Machine Learning Datasets 52

Knowledge Hut

MAY 31, 2023

Whether you are a beginner or an experienced programmer, these top database projects with source codes can help you improve your skills and add value to your portfolio. Using MongoDB, you can build a product catalog management system that can handle large amounts of data and provide real-time insights to users.

Database 52

Database Coding MongoDB Project 52

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

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. How do you Create a Good Big Data Project?

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

AUGUST 24, 2021

Thus, as a learner, your goal should be to work on projects that help you explore structured and unstructured data in different formats. Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. A data engineer interacts with this warehouse almost on an everyday basis.

Data Engineering 52

Data Engineering Data Engineer Coding Project 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 17, 2021

Building a portfolio of projects will give you the hands-on experience and skills required for performing sentiment analysis. Access the Sentiment Analysis Project on Product Reviews with Source Code Get FREE Access to Machine Learning Example Codes for Data Cleaning, Data Munging, and Data Visualization 2.

Coding 52

Coding Project Entertainment Datasets 52

ProjectPro

DECEMBER 7, 2021

Table of Contents What is a Data Pipeline? The Importance of a Data Pipeline What is an ETL Data Pipeline? What is a Big Data Pipeline? Features of a Data Pipeline Data Pipeline Architecture How to Build an End-to-End Data Pipeline from Scratch? What is a Big Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Knowledge Hut

NOVEMBER 16, 2023

The increased accessibility of online professional courses and authentic study resources has contributed significantly to bringing up the number of skilled workforces. Their main responsibilities include processing data, identifying valuable data sources, combining models, integrating data, etc. billion on IT in 2022.

IT 52

IT Software Engineer Software Engineering Cloud Computing 52

U-Next

OCTOBER 26, 2022

It mainly focuses on building systems that perform based on the input data without requiring numerous human interventions such as coding, etc. AI assesses unstructured data about potentially dangerous actions or activities in an organization’s operations. Portfolio Development . Risk Management .

Finance 40

Finance Portfolio Banking Algorithm 40

Knowledge Hut

MARCH 26, 2024

Solution architects work with developers, stakeholders, and other IT specialists to build unified and effective systems. Responsibilities: Define data architecture strategies and roadmaps to support business objectives and data initiatives. Design data models, schemas, and storage solutions for structured and unstructured data.

Amazon Web Services 52

Amazon Web Services Google Cloud Computer Science AWS 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

AltexSoft

JUNE 7, 2021

As a result, a Big Data analytics task is split up, with each machine performing its own little part in parallel. Hadoop hides away the complexities of distributed computing, offering an abstracted API to get direct access to the system’s functionality and its benefits — such as. High latency of data access. scalability.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Knowledge Hut

FEBRUARY 7, 2023

They help spread data science work by getting non-expert data scientists into the model-building process, offering drag-and-drop interfaces. Proprietary (Often GUI-driven) Data Science Platforms Proprietary tools support a lot of use cases, including data science and model building.

Data Science 52

Data Science Google Cloud AWS Programming Language 52

Edureka

JULY 18, 2023

These techniques add an additional degree of security and make it more difficult for unauthorised people to access private user accounts. maintain secure access and stop unauthorised actions, these systems continuously analyse device behaviour, spot possible risks, and implement security measures.

Banking 40

Banking Algorithm Media Machine Learning 40

ProjectPro

NOVEMBER 30, 2021

The crux of all data-driven solutions or business decision-making lies in how well the respective businesses collect, transform, and store data. When working on real-time business problems, data scientists build models using various Machine Learning or Deep Learning algorithms. You may get an unexpected result.

Process 52

Process Data Pipeline Data Warehouse AWS 52

ProjectPro

JANUARY 24, 2023

With BigQuery, users can process and analyze petabytes of data in seconds and get insights from their data quickly and easily. Moreover, BigQuery offers a variety of features to help users quickly analyze and visualize their data. It provides powerful query capabilities for running SQL queries to access and analyze data.

Bytes 52

Bytes Google Cloud Data Warehouse Datasets 52

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.

NoSQL 52

NoSQL Database Hadoop Big Data 52

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. Data Scientists use ML algorithms to make predictions on the data sets.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

ProjectPro

JUNE 24, 2021

Here is the list of key technical skills required for analytics job roles which can also be acquired by students or professionals from a non- technical background - SQL : Structured Query Language is required to query data present in databases. Even data that has to be filtered, will have to be stored in an updated location.

Data Analytics 40

Data Analytics Project Insurance Hadoop 40

ProjectPro

DECEMBER 7, 2016

In this case, the analytical use case can be accomplished using apache hive and results of analytics need to be stored in HBase for random access. Hive and HBase are both data stores for storing unstructured data. Explore SQL Database Projects to Add them to Your Data Engineer Resume.

Technology 40

Technology NoSQL Hadoop Data Mining 40

AltexSoft

MAY 14, 2021

Data generated from various sources including sensors, log files and social media, you name it, can be utilized both independently and as a supplement to existing transactional data many organizations already have at hand. Data storage and processing. NoSQL databases.

Big Data 78

Big Data Data Analytics IT NoSQL 78

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 Hadoop for leveraging analytics.

Hadoop 52

Hadoop Unstructured Data Big Data Retail 52

ProjectPro

MARCH 15, 2016

Table of Contents Hadoop Distributed File System (HDFS) Hadoop MapReduce Hadoop in the Financial Sector Hadoop in Healthcare Sector Hadoop for Telecom Industry Hadoop in Retail Sector Hadoop for Building Recommendation System Studying Hadoop use cases will help to – 1.)

Hadoop 40

Hadoop Retail Healthcare Banking 40

ProjectPro

AUGUST 11, 2021

The data warehouse layer consists of the relational database management system (RDBMS) that contains the cleaned data and the metadata, which is data about the data. The RDBMS can either be directly accessed from the data warehouse layer or stored in data marts designed for specific enterprise departments.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 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. Even if ETL fades into oblivion, it will not be a binary change.

Hadoop 52

Hadoop Unstructured Data ETL Tools ETL System 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 allows us to store data that we never stored before.

Hadoop 52

Hadoop Big Data Data Analytics Banking 52

ProjectPro

SEPTEMBER 14, 2016

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. Assess the quality of datasets for a hadoop data lake. Defining Hadoop Job Flows.

Hadoop 40

Hadoop Unstructured Data Java Big Data 40

ProjectPro

DECEMBER 10, 2021

Azure Cloud Services are hosted on virtual machines, and they let one have a higher degree of control over the VMs by allowing software installation on the VMs and also making them remotely accessible. A user only pays for the resources he needs from a cloud service provider and accesses them over a secure Internet connection.

BI 52

BI Cloud Computing SQL Database 52

AltexSoft

MAY 5, 2023

Machine Learning is a subset of AI involving the design of algorithms that enable computers to learn patterns within historical data and make predictions or decisions based on new information. Deep Learning is a subset of machine learning that focuses on building complex algorithms named deep neural networks.

Machine Learning 59

Machine Learning Hospitality Algorithm Deep Learning 59

ProjectPro

JULY 3, 2015

SAP intends to develop a deeper integration with Apache Hadoop by using Apache Spark as the data filtering mechanism.Apache Spark can be used as in-memory analysis and data streaming platform (intelligent processing engine) for speeded up data access in Hadoop. Table of Contents How SAP Hadoop work together?

Hadoop 40

Hadoop Big Data Data Solutions Unstructured Data 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 Warehouses do not retain all data whereas Data Lakes do.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40