Cloudera

DECEMBER 14, 2021

Department of Treasury that needs to quickly analyze petabytes of data across hundreds of servers. So to improve the speed of data analysis, the IRS worked with the combined technology integrating Cloudera Data Platform (CDP) and NVIDIA’s RAPIDS Accelerator for Apache Spark 3.0. You can become a data hero too.

Transportation 111

Transportation Telecommunication Banking Data Lake 111

Rockset

AUGUST 4, 2021

With Snowflake, organizations get the simplicity of data management with the power of scaled-out data and distributed processing. Although Snowflake is great at querying massive amounts of data, the database still needs to ingest this data. Data ingestion must be performant to handle large amounts of data.

Data Ingestion 40

Data Ingestion Cloud Storage Data Warehouse Architecture 40

phData: Data Engineering

FEBRUARY 21, 2025

A data warehouse enables advanced analytics, reporting, and business intelligence. The data warehouse emerged as a means of resolving inefficiencies related to data management, data analysis, and an inability to access and analyze large volumes of data quickly.

Cloud 52

Cloud Data Warehouse Amazon Web Services Data Ingestion 52

Snowflake

JUNE 6, 2024

Faster, easier AI/ML and data engineering workflows Explore, analyze and visualize data using Python and SQL. Discover valuable business insights through exploratory data analysis. Develop scalable data pipelines and transformations for data engineering.

SQL 115

SQL Python Machine Learning Data Workflow 115

Cloudera

MAY 19, 2021

RAPIDS on the Cloudera Data Platform comes pre-configured with all the necessary libraries and dependencies to bring the power of RAPIDS to your projects. RAPIDS brings the power of GPU compute to standard Data Science operations, be it exploratory data analysis, feature engineering or model building. Data Ingestion.

Machine Learning 137

Machine Learning Data Science Datasets Raw Data 137

Cloudera

JULY 9, 2021

Use the right tools: Organizations must command and control the entire data lifecycle, from initial data ingest to AI/ML based analysis to acting decisively on data-driven intelligence derived from newfound, cloud-enabled impact, the right capabilities produce the holistic, coherent view that drives organizations to the cloud in the first place.

Government 114

Government Building Cloud Data Ingestion 114

Cloudera

NOVEMBER 17, 2020

The data and the techniques presented in this prototype are still applicable as creating a PCA feature store is often part of the machine learning process. . The process followed in this prototype covers several steps that you should follow: Data Ingest – move the raw data to a more suitable storage location.

Deep Learning 115

Deep Learning Machine Learning Raw Data Data Ingestion 115

Cloudera

APRIL 20, 2021

Streaming Analytics is a type of data analysis that processes data streams for real-time analytics. It continuously processes data from multiple streams and performs simple calculations to complex event processing for delivering sophisticated use cases. What is Streaming Analytics? What is modern streaming architecture?

Kafka 95

Kafka Hospitality Retail Data Ingestion 95

Striim

SEPTEMBER 11, 2024

Data Collection/Ingestion The next component in the data pipeline is the ingestion layer, which is responsible for collecting and bringing data into the pipeline. By efficiently handling data ingestion, this component sets the stage for effective data processing and analysis.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Knowledge Hut

JANUARY 18, 2024

Data Science initiatives from an operational standpoint help organizations optimize various aspects of their business, such as supply chain management , inventory segregation, and management, demand forecasting, etc. A data analyst would be a professional who will be able to accomplish all the tasks mentioned in the process of data analysis.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

Snowflake

NOVEMBER 29, 2023

While the former can be solved by tokenization strategies provided by external vendors, the latter mandates the need for patient-level data enrichment to be performed with sufficient guardrails to protect patient privacy, with an emphasis on auditability and lineage tracking.

Metadata 114

Metadata Healthcare Medical Data Storage 114

Snowflake

AUGUST 8, 2023

Some of the more interesting use cases include: Customer service triage, response generation, and eventually full-chat experiences, as described above Advertising creative generation personalized for each customer, based on everything you know about each customer in Snowflake SQL-drafting and question-answering data analysis chatbots based on your (..)

Generalist 98

Generalist Data Ingestion SQL Technology 98

Cloudera

FEBRUARY 9, 2021

Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability.

Data Warehouse 72

Data Warehouse Cloud Kafka Cloud Storage 72

Knowledge Hut

APRIL 23, 2024

As organizations strive to gain valuable insights and make informed decisions, two contrasting approaches to data analysis have emerged, Big Data vs Small Data. These contrasting approaches to data analysis are shaping the way organizations extract insights, make predictions, and gain a competitive edge.

Big Data 52

Big Data Datasets Data Analysis Media 52

Striim

JUNE 6, 2024

Inability to leverage AI/ML to its fullest potential: Because artificial intelligence and machine learning algorithms heavily lean on large volumes of real-time data to generate insights, your business is unable to use these technologies to their fullest potential without low latency data integration and streaming.

Data Integration 52

Data Integration Data Ingestion Healthcare Data Pipeline 52

ProjectPro

AUGUST 24, 2021

To understand their requirements, it is critical to possess a few basic data analytics skills to summarize the data better. So, add a few beginner-level data analytics projects to your resume to highlight your Exploratory Data Analysis skills. This big data project discusses IoT architecture with a sample use case.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Knowledge Hut

JUNE 26, 2023

If you want to break into the field of data engineering but don't yet have any expertise in the field, compiling a portfolio of data engineering projects may help. Data pipeline best practices should be shown in these initiatives. In addition to this, they make sure that the data is always readily accessible to consumers.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Snowflake

MARCH 13, 2023

Architecture designed to empower more clients Gem’s cybersecurity platform starts with raw data ingestion from its clients’ cloud environments. Gem uses the fully-managed Snowpipe service, allowing it to stream and process source data in near-real time. Pushing and scaling are super smooth.

Cloud 52

Cloud Building Data Ingestion AWS 52

Edureka

FEBRUARY 9, 2023

As the demand for data engineers grows, having a well-written resume that stands out from the crowd is critical. Azure data engineers are essential in the design, implementation, and upkeep of cloud-based data solutions. It is also crucial to have experience with data ingestion and transformation.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Snowflake

OCTOBER 21, 2024

These integrations empower organizations to utilize their Snowflake AI Data Cloud datasets directly within Adobe’s marketing and analytics ecosystem, facilitating seamless operations from data enrichment to querying for personalized campaigns.

Data Ingestion 52

Data Ingestion BI Government Datasets 52

Knowledge Hut

NOVEMBER 2, 2023

Top 10 Azure Data Engineering Project Ideas for Beginners For beginners looking to gain practical experience in Azure Data Engineering, here are 10 Azure Data engineer real time projects ideas that cover various aspects of data processing, storage, analysis, and visualization using Azure services: 1.

Data Engineering 52

Data Engineering Data Engineer Project Coding 52

Knowledge Hut

APRIL 23, 2024

It encompasses data from diverse sources such as social media, sensors, logs, and multimedia content. The key characteristics of big data are commonly described as the three V's: volume (large datasets), velocity (high-speed data ingestion), and variety (data in different formats).

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Knowledge Hut

SEPTEMBER 26, 2023

Whether you're running ad-hoc queries or performing complex data transformations, Azure Synapse ensures that your analytics are conducted swiftly, enabling timely decision-making. It supports a variety of query languages, including the industry-standard SQL, as well as popular data analysis languages like Python and R.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

ProjectPro

OCTOBER 28, 2015

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

RandomTrees

SEPTEMBER 27, 2024

In Data Factory, describe your data ingestion and transformation needs using natural language, and Copilot will handle the rest. When working in a notebook in Data Engineering or Data Science, use Copilot to quickly enrich, model, analyse, and explore your data.

Database-centric 52

Database-centric Pipeline-centric IT BI 52

AltexSoft

MAY 12, 2023

This article delves into the realm of unstructured data, highlighting its importance, and providing practical guidance on extracting valuable insights from this often-overlooked resource. We will discuss the different data types, storage and management options, and various techniques and tools for unstructured data analysis.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

AltexSoft

MAY 14, 2021

Big Data analytics encompasses the processes of collecting, processing, filtering/cleansing, and analyzing extensive datasets so that organizations can use them to develop, grow, and produce better products. Big Data analytics processes and tools. Data ingestion. Data analysis.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Knowledge Hut

DECEMBER 13, 2023

Tiger Analytics Tiger Analytics is among the important big data analytics companies. Tiger Analytics is a global leader in data analytics, and they provide organizations with a variety of data analysis options. Tech Mahindra Tech Mahindra is a service-based company with a data-driven focus.

Big Data 52

Big Data Consulting Hadoop Amazon Web Services 52

AltexSoft

MARCH 30, 2023

Databricks architecture Databricks provides an ecosystem of tools and services covering the entire analytics process — from data ingestion to training and deploying machine learning models. Besides that, it’s fully compatible with various data ingestion and ETL tools. Let’s see what exactly Databricks has to offer.

Scala 64

Scala Data Lake Machine Learning BI 64

Monte Carlo

NOVEMBER 14, 2023

These issues can look like: Data inconsistency: Tables with both raw and transformed data or both frequently updated data and stale data – affecting the accuracy of data analysis and reporting.

Data Lake 64

Data Lake Metadata Data Warehouse SQL 64

AltexSoft

AUGUST 29, 2023

Examples of unstructured data can range from sensor data in the industrial Internet of Things (IoT) applications, videos and audio streams, images, and social media content like tweets or Facebook posts. Data ingestion Data ingestion is the process of importing data into the data lake from various sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

APRIL 25, 2024

It is the right time to skill yourself in spatial data science cases, applications, and various elements. This article gives overview of spatial data science’s elements, use cases, types of spatial data analysis, and it’s application. The Data Science market is growing so does job opportunities.

Data Science 52

Data Science Telecommunication Transportation Big Data 52

Knowledge Hut

DECEMBER 7, 2023

Power BI is a powerful business intelligence tool developed by Microsoft that enables users to transform raw data into interactive and visually appealing insights. It caters to data analysis and visualization needs, aiding in making informed business decisions.

BI 52

BI Raw Data Datasets Business Intelligence 52

Precisely

SEPTEMBER 11, 2023

” Solution: Intelligent solutions can mine metadata, analyze usage patterns and frequencies, and identify relationships among data elements – all through automation, with minimal human input. Problem: “We face challenges in manually classifying, cataloging, and organizing large volumes of data.”

Metadata 52

Metadata Data Integration Datasets Data Analysis Tools 52

Snowflake

JULY 18, 2023

Data infrastructure that makes light work of complex tasks Built as a connected application from day one, the anecdotes Compliance OS uses the Snowflake Data Cloud for data ingestion and modeling, including a single cybersecurity data lake where all data can be analyzed within Snowflake.

Data Process 52

Data Process Process Data Lake Data Ingestion 52

ProjectPro

OCTOBER 14, 2016

What is important is not from where a professional has got the hadoop certification but what they have learnt while achieving the big data certification, regardless of whether it is from Cloudera, Hortonworks, MapR or any other vendor.

Hadoop 52

Hadoop Certification Recruitment Big Data 52

Silectis

JANUARY 3, 2021

BI (Business Intelligence) Strategies and systems used by enterprises to conduct data analysis and make pertinent business decisions. Big Data Large volumes of structured or unstructured data. Data Engineering Data engineering is a process by which data engineers make data useful.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40