Snowflake

MARCH 18, 2024

This time it’s all about ensuring that the data and the platform where it’s processed are ready for the new AI models. But there’s still a long way to go in an environment where the volume, velocity and complexity of data and data types is constantly increasing. But lowering the barriers also raises the risks.

Unstructured Data 87

Unstructured Data Government Data Pipeline Cloud 87

Cloudera

APRIL 1, 2024

The following are key attributes of our platform that set Cloudera apart: Unlock the Value of Data While Accelerating Analytics and AI The data lakehouse revolutionizes the ability to unlock the power of data. Data that has lineage so you can trace back the source and all the processing it underwent.

Cloud 104

Cloud Unstructured Data Metadata Datasets 104

Snowflake

JANUARY 24, 2024

For example, to inform policy decisions, an LLM-trained chatbot can tunnel through mountains of otherwise difficult-to-access social and economic data to locate answers quickly, and make them accessible to all—not just those with technical skills. This will be enabled in the U.S.

Government 98

Government Data Management Cloud Data 98

Data Engineering Weekly

MAY 5, 2024

The motivation for Machine Unlearning is critical from the privacy perspective and for model correction, fixing outdated knowledge, and access revocation of the training dataset. The author expands on the possibility of unified data platforms. A key thought-provoking moment for me while reading the article is this quote.

Data Engineering 67

Data Engineering Data Engineer Engineering Google Cloud 67

ProjectPro

JANUARY 25, 2022

PySpark is a handy tool for data scientists since it makes the process of converting prototype models into production-ready model workflows much more effortless. PySpark is used to process real-time data with Kafka and Streaming, and this exhibits low latency. Why use PySpark? To set the master URL, use setMaster(value).

Big Data 52

Big Data Data Process Process Kafka 52

Snowflake

NOVEMBER 2, 2023

Rather than defining schema upfront, a user can decide which data and schema they need for their use case. Snowflake has long supported semi-structured data types and file formats like JSON, XML, Parquet, and more recently storage and processing of unstructured data such as PDF documents, images, videos, and audio files.

Data Lake 91

Data Lake Data Warehouse Cloud Unstructured Data 91

Knowledge Hut

FEBRUARY 29, 2024

Get to know more about data science for business. Learning Data Analysis in Excel Data analysis is a process of inspecting, cleaning, transforming and modelling data with an objective of uncover the useful knowledge, results and supporting decision. The best Website to learn Python: w3schools.com.

Data Science 98

Data Science Datasets Database Design Machine Learning 98

AltexSoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general. GraphX is Spark’s component for processing graph data.

Big Data 52

Big Data Data Process Process Hadoop 52

Knowledge Hut

MARCH 20, 2024

Data type defines the kind of value that can be stored in a variable or expression, acting as a classification system for data. Data structure, on the other hand, is a way to arrange and store data in computer memory so that it may be accessed and altered quickly. What is Data Structure?

Computer Science 52

Computer Science Programming Language Algorithm Software Engineer 52

Knowledge Hut

APRIL 23, 2024

These data sets consist of extensive and intricate data from diverse sources, including business transactions, social media interactions, and sensor data. Big data stands out due to its significant volume, quick velocity, and wide variety, leading to difficulties in storage, processing, analysis, and interpretation.

Big Data 52

Big Data Media Datasets Unstructured Data 52

Knowledge Hut

JANUARY 29, 2024

In today's data-driven world, where information reigns supreme, businesses rely on data to guide their decisions and strategies. However, the sheer volume and complexity of raw data from various sources can often resemble a chaotic jigsaw puzzle.

Raw Data 52

Raw Data Data Mining Data Preparation Structured Data 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. Integration issues: Complex processes often involve interacting with multiple systems and applications.

Unstructured Data 57

Unstructured Data Government Data Validation Programming 57

AltexSoft

MAY 12, 2023

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc. doc,docx), PDF files (.pdf),

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Knowledge Hut

APRIL 23, 2024

Data warehouses are typically built using traditional relational database systems, employing techniques like Extract, Transform, Load (ETL) to integrate and organize data. Data warehousing offers several advantages. By structuring data in a predefined schema, data warehouses ensure data consistency and accuracy.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Knowledge Hut

MAY 3, 2024

Perform iteration with enumerate() instead of range() Consider a situation during a coding interview: You have a list of elements, and you have to iterate over the list with the access to both the indices and values. Initially, your program might work well but it will gradually slow down and the process will be changed completely.

Python 98

Python Coding Data Programming 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. It is utilized for all types of storage and processing needs.

Database 52

Database NoSQL Management Relational Database 52

Knowledge Hut

MARCH 22, 2024

On the other hand, in non-linear data structures, the elements do not form a sequence. The choice between using a linear or non-linear data structure depends on the access patterns needed for the application. More flexible in terms of data organisation and access. Easier to understand and implement.

Algorithm 52

Algorithm Data Datasets Accessible 52

Striim

MAY 1, 2024

UPS Capital recognizes the challenges faced by its customers in securing their package delivery ecosystem and is harnessing digital capabilities and data access to redefine traditional approaches, ensuring improved customer experiences and combating shipping loss.

Google Cloud 52

Google Cloud Insurance Finance Machine Learning 52

Snowflake

MARCH 30, 2023

Collecting, cleaning, and organizing data into a coherent form for business users to consume are all standard data modeling and data engineering tasks for loading a data warehouse. Schema drift on a wide table structure needs an ALTER TABLE statement, whereas the tall table structure does not.

Engineering 84

Engineering Raw Data Data Science Scala 84

Towards Data Science

DECEMBER 23, 2023

Photo by Ian Taylor on Unsplash This tutorial guides you through an analytics use case, analyzing semi-structured data with Spark SQL. We’ll start with the data engineering process, pulling data from an API and finally loading the transformed data into a data lake (represented by MinIO ).

SQL 73

SQL Data Analytics Hadoop Raw Data 73

Knowledge Hut

JANUARY 30, 2024

Whether you're a seasoned data scientist or just stepping into the world of data, come with me as we unravel the secrets of data extraction and learn how it empowers us to unleash the full potential of data. What is data extraction? Primary Focus Structuring and preparing data for further analysis.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Snowflake

SEPTEMBER 19, 2023

Why AI has everyone’s attention, what it means for different data roles, and how Alteryx and Snowflake are bringing AI to data use cases There’s a llama on the loose! With all the hoopla around AI, there’s a lot to get up to speed on—especially the implications this technology has for data analytics.

Machine Learning 95

Machine Learning Unstructured Data Data Analytics Government 95

Monte Carlo

JULY 13, 2023

To effectively manage and analyze this data, data engineering teams must navigate a wide range of challenges, including data access, security, compliance, and data observability. Automation is a missing link in many organizations’ efforts toward data operationalization. Automating self-service access.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

Knowledge Hut

APRIL 25, 2024

Information Technology is a field that manages and processes information for large-scale organizations or companies. Information Technology uses computer systems or devices to access information. Global companies incline towards using Information Technology to manage and innovate data according to their processes.

Technology 52

Technology Recruitment Media Cloud Computing 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 Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

ThoughtSpot

MARCH 5, 2024

When creating a dynamic table in Snowflake, you specify the SQL query that will transform the source data. The refresh process automatically computes changes in the source data and merges those updates into the dynamic table. To power these refreshes, compute resources are associated with each dynamic table.

BI 94

BI Datasets Raw Data SQL 94

U-Next

SEPTEMBER 7, 2022

Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. To provide meaningful business insights, it collects and manages data from a variety of sources. In other words, it is the process of converting data into information. .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Knowledge Hut

APRIL 23, 2024

Data storing and processing is nothing new; organizations have been doing it for a few decades to reap valuable insights. Compared to that, Big Data is a much more recently derived term. So, what exactly is the difference between Traditional Data and Big Data? Smaller and more cost-effective ways of managing data.

Big Data 52

Big Data Relational Database Data Datasets 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. Quality : Is the data itself anomalous?

Database 72

Database Unstructured Data Data Pipeline Metadata 72

Ascend.io

FEBRUARY 28, 2024

Engineers ensure the availability of clean, structured data, a necessity for AI systems to learn from patterns, make accurate predictions, and automate decision-making processes. By ensuring data is well-organized and readily accessible, data engineers empower AI systems to deliver targeted and effective solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

Cloudera

JUNE 3, 2022

Due to the lack of tooling specifically designed for data discovery, exploration, and preliminary analysis, this presents a significant challenge for these teams. . When it comes to the early stages in the data science process, data scientists often find themselves jumping between a wide range of tooling.

Data Analysis 90

Data Analysis PostgreSQL Data Science SQL 90

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

Snowflake

JULY 24, 2023

Around 1500 people across a wide range of roles, from accountants and financial controllers to top-level managers, rely on Fortum’s financial data, meaning it has to be highly accessible while remaining completely secure and compliant. Our data infrastructure had simply reached the end of its life.”

Building 52

Building Engineering Finance Data Lake 52

Knowledge Hut

APRIL 25, 2024

One of the industries with the quickest growth rates is big data. It refers to gathering and processing sizable amounts of data to produce insights that may be used by an organization to improve its various facets. 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