Knowledge Hut

APRIL 23, 2024

Big Data vs Small Data: Volume Big Data refers to large volumes of data, typically in the order of terabytes or petabytes. It involves processing and analyzing massive datasets that cannot be managed with traditional data processing techniques.

Big Data 52

Big Data Datasets Data Analysis Media 52

Knowledge Hut

SEPTEMBER 26, 2023

Organisations are constantly looking for robust and effective platforms to manage and derive value from their data in the constantly changing landscape of data analytics and processing. These platforms provide strong capabilities for data processing, storage, and analytics, enabling companies to fully use their data assets.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Data Engineering Weekly

AUGUST 4, 2024

It also introduces innovative constrained generation techniques that promise to revolutionize how we approach structured data generation. We look at efficiency in data processing within a single node, which increases the momentum for systems like DuckDB, Arrow, and Polaris.

Data Engineer 80

Data Engineer Data Engineering Engineering Data 80

Edureka

JULY 4, 2024

Choose Amazon S3 for cost-efficient storage to store and retrieve data from any cluster. It provides an efficient and flexible way to manage the large computing clusters that you need for data processing, balancing volume, cost, and the specific requirements of your big data initiative.

AWS 52

AWS Amazon Web Services Hadoop Big Data 52

Data Engineering Weekly

JULY 14, 2024

(Senior Solutions Architect at AWS) Learn about: Efficient methods to feed unstructured data into Amazon Bedrock without intermediary services like S3. Techniques for turning text data and documents into vector embeddings and structured data. Streaming execution to process a small chunk of data at a time.

Data Engineer 98

Data Engineer Data Engineering Engineering Unstructured Data 98

Knowledge Hut

JUNE 28, 2023

Focus Exploration and discovery of hidden patterns and trends in data. Reporting, querying, and analyzing structured data to generate actionable insights. Data Sources Diverse and vast data sources, including structured, unstructured, and semi-structured data.

Data Mining 52

Data Mining Business Intelligence BI Structured Data 52

The Modern Data Company

MAY 10, 2023

To choose the most suitable data management solution for your organization, consider the following factors: Data types and formats: Do you primarily work with structured, unstructured, or semi-structured data? Consider whether you need a solution that supports one or multiple data formats.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

Monte Carlo

NOVEMBER 21, 2024

Think of it as the “slow and steady wins the race” approach to data processing. Stream Processing Pattern Now, imagine if instead of waiting to do laundry once a week, you had a magical washing machine that could clean each piece of clothing the moment it got dirty. The data lakehouse has got you covered!

Data Pipeline 52

Data Pipeline Designing Lambda Architecture Kafka 52

Knowledge Hut

MAY 2, 2024

To store and process even only a fraction of this amount of data, we need Big Data frameworks as traditional Databases would not be able to store so much data nor traditional processing systems would be able to process this data quickly. Spark can be used interactively also for data processing.

Hadoop 96

Hadoop Scala Datasets Java 96

The Modern Data Company

MAY 10, 2023

To choose the most suitable data management solution for your organization, consider the following factors: Data types and formats: Do you primarily work with structured, unstructured, or semi-structured data? Consider whether you need a solution that supports one or multiple data formats.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

To choose the most suitable data management solution for your organization, consider the following factors: Data types and formats: Do you primarily work with structured, unstructured, or semi-structured data? Consider whether you need a solution that supports one or multiple data formats.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

U-Next

MARCH 1, 2023

Being a hybrid role, Data Engineer requires technical as well as business skills. They build scalable data processing pipelines and provide analytical insights to business users. A Data Engineer also designs, builds, integrates, and manages large-scale data processing systems. What is AWS Kinesis?

Data Engineer 75

Data Engineer Data Engineering Non-relational Database Engineering 75

Striim

OCTOBER 11, 2024

While legacy ETL has a slow transformation step, modern ETL platforms, like Striim, have evolved to replace disk-based processing with in-memory processing. This advancement allows for real-time data transformation , enrichment, and analysis, providing faster and more efficient data processing.

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 52

Pinterest Engineering

NOVEMBER 28, 2023

Pinterest’s real-time metrics asynchronous data processing pipeline, powering Pinterest’s time series database Goku, stood at the crossroads of opportunity. The mission was clear: identify bottlenecks, innovate relentlessly, and propel our real-time analytics processing capabilities into an era of unparalleled efficiency.

Kafka 96

Kafka Bytes Architecture Software Engineer 96

Knowledge Hut

APRIL 25, 2023

Database management: Data engineers should be proficient in storing and managing data and working with different databases, including relational and NoSQL databases. Data modeling: Data engineers should be able to design and develop data models that help represent complex data structures effectively.

Data Engineer 52

Data Engineer Data Engineering Engineering Google Cloud 52

Knowledge Hut

MAY 2, 2024

It also supports a rich set of higher-level tools, including Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming. It provides high-level APIs in Java, Scala, Python, and R and an optimized engine that supports general execution graphs.

Java 98

Java Hadoop Scala SQL 98

Knowledge Hut

JULY 24, 2023

NoSQL Databases NoSQL databases are non-relational databases (that do not store data in rows or columns) more effective than conventional relational databases (databases that store information in a tabular format) in handling unstructured and semi-structured data.

Database 52

Database NoSQL Management Relational Database 52

Snowflake

AUGUST 19, 2024

Automatic Clustering, Materialized Views and Search Optimization are major examples of this, and they all accelerate your queries via intelligent data-processing techniques. Based on internal Snowflake data, query duration for customers’ stable workloads improved by 27% from Aug. 25, 2022 to April 30, 2024.

BI 52

BI Data Ingestion Structured Data Engineering 52

Precisely

APRIL 30, 2024

RPA is best suited for simple tasks involving consistent data. It’s challenged by complex data processes and dynamic environments Complete automation platforms are the best solutions for complex data processes. These include: Structured data dependence: RPA solutions thrive on well-organized, predictable data.

Unstructured Data 59

Unstructured Data Government Data Validation Programming 59

Striim

MAY 1, 2024

The sheer volume of data generated from the increasing package deliveries overwhelmed existing data management systems, underscoring a critical need for more advanced data handling capabilities. The absence of real-time data processing capabilities hindered UPS Capital’s risk management and rapid response efforts.

Google Cloud 52

Google Cloud Insurance Finance Machine Learning 52

Monte Carlo

FEBRUARY 12, 2024

To differentiate and expand the usefulness of these models, organizations must augment them with first-party data – typically via a process called RAG (retrieval augmented generation). Today, this first-party data mostly lives in two types of data repositories.

Database 72

Database Unstructured Data Data Pipeline Metadata 72

Monte Carlo

MAY 28, 2024

This involves connecting to multiple data sources, using extract, transform, load ( ETL ) processes to standardize the data, and using orchestration tools to manage the flow of data so that it’s continuously and reliably imported – and readily available for analysis and decision-making.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

The Modern Data Company

MAY 8, 2023

It can store any type of data — structured, unstructured, and semi-structured — in its native format, providing a highly scalable and adaptable solution for diverse data needs. Data is stored in a schema-on-write approach, which means data is cleaned, transformed, and structured before storing.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

It can store any type of data — structured, unstructured, and semi-structured — in its native format, providing a highly scalable and adaptable solution for diverse data needs. Data is stored in a schema-on-write approach, which means data is cleaned, transformed, and structured before storing.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

It can store any type of data — structured, unstructured, and semi-structured — in its native format, providing a highly scalable and adaptable solution for diverse data needs. Data is stored in a schema-on-write approach, which means data is cleaned, transformed, and structured before storing.

Data Management 52

Data Management Management Data Lake Data Governance 52

Snowflake

MARCH 14, 2024

Glue provides a simple, direct way for organizations with SAP systems to quickly and securely ingest SAP data into Snowflake. It sits on the application layer within SAP, which makes almost any structured data accessible and available for change data capture (CDC).

IT 97

IT Data Ingestion Data AWS 97

Snowflake

NOVEMBER 11, 2024

These scalable models can handle millions of records, enabling you to efficiently build high-performing NLP data pipelines. However, scaling LLM data processing to millions of records can pose data transfer and orchestration challenges, easily addressed by the user-friendly SQL functions in Snowflake Cortex.

Unstructured Data 52

Unstructured Data SQL AWS Healthcare 52

Knowledge Hut

MARCH 20, 2024

What is Data Structure? Data structure is a method for effectively accessing and manipulating data by arranging and storing it in a computer's memory. Data Structure: Memory Representation Data Type Data types define the type of data a variable can hold.

Computer Science 52

Computer Science Programming Language Algorithm Software Engineer 52

Snowflake

JUNE 5, 2024

Cortex AI Cortex Analyst: Enable business users to chat with data and get text-to-answer insights using AI Cortex Analyst, built with Meta’s Llama 3 and Mistral Large models, lets you get the insights you need from your structured data by simply asking questions in natural language.

Coding 91

Coding Building Management Government 91

Snowflake

JULY 10, 2023

“California Air Resources Board has been exploring processing atmospheric data delivered from four different remote locations via instruments that produce netCDF files. Previously, working with these large and complex files would require a unique set of tools, creating data silos.

Unstructured Data 40

Unstructured Data Python Process Scala 40

Edureka

AUGUST 2, 2023

It is a crucial tool for data scientists since it enables users to create, retrieve, edit, and delete data from databases.SQL (Structured Query Language) is indispensable when it comes to handling structured data stored in relational databases. Data scientists use SQL to query, update, and manipulate data.

Programming Language 52

Programming Language Programming Scala Pharmaceutical 52

Monte Carlo

AUGUST 25, 2023

Understanding data warehouses A data warehouse is a consolidated storage unit and processing hub for your data. Teams using a data warehouse usually leverage SQL queries for analytics use cases. This same structure aids in maintaining data quality and simplifies how users interact with and understand the data.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Databand.ai

JULY 17, 2023

MLOps: Key Similarities and Differences Similarities between DataOps and MLOps Focus on collaboration: Both methodologies emphasize the importance of cross-functional teams working together to improve data processes, including data scientists, engineers, analysts, and business stakeholders.

Data Pipeline 52

Data Pipeline Machine Learning High Quality Data BI 52

ProjectPro

AUGUST 11, 2021

This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data from data warehouses is queried using SQL.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Monte Carlo

OCTOBER 10, 2024

Handling unstructured data Many AI models are fed large amounts of unstructured data, making data quality management complex. AI Data Quality Analysts must be able to monitor unstructured data for anomalies before it’s turned into structured data within an LLM.

Unstructured Data 52

Unstructured Data Google Cloud Machine Learning ETL Tools 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 Engineer 52

Data Engineer Data Engineering Engineering Medical 52

AltexSoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Obviously, Big Data processing involves hundreds of computing units.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98