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? Data Size Much larger in size, volume, and variety.

Big Data 52

Big Data Relational Database Data Datasets 52

Snowflake

MARCH 14, 2024

But SAP has limited analytics capabilities, and directly ingesting SAP data into Snowflake can present a challenge. Changes to SAP’s warehousing strategy over time mean many customers may need to patch together and manage multiple technologies to extract data in a useful format. What’s the challenge with unlocking SAP data?

IT 90

IT Data Ingestion Data AWS 90

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

Knowledge Hut

JANUARY 29, 2024

So, join us on this enlightening journey as we demystify Data Wrangling and reveal how it empowers businesses to harness the true potential of their data. What Is Data Wrangling? Data Wrangling, often referred to as Data Munging, is a fundamental process in the world of data analysis and management.

Raw Data 52

Raw Data Data Mining Data Preparation Structured Data 52

ThoughtSpot

MARCH 5, 2024

Managing complex data pipelines is a major challenge for data-driven organizations looking to accelerate analytics initiatives. Create Snowflake dynamic tables In Snowflake, create dynamic tables by writing SQL queries that define how data should be transformed and materialized. Now, that’s changing.

BI 94

BI Datasets Raw Data SQL 94

Snowflake

JULY 27, 2023

Founded in 2014, the company’s vision is to make incredible homes easily accessible to everyone. After we had a successful trial period that checked all the boxes, we started our migration in autumn 2021 — together with moving all our data transformation management into the OSS version of dbt.

Data Architecture 52

Data Architecture Architecture Building Structured Data 52

Precisely

APRIL 30, 2024

Even with all of the technological advances introduced over the past few decades, many of the data creation and management processes used by businesses today are highly manual – meaning they’re slow, ungoverned, and error-prone. These include: Structured data dependence: RPA solutions thrive on well-organized, predictable data.

Unstructured Data 59

Unstructured Data Government Data Validation Programming 59

Knowledge Hut

APRIL 23, 2024

These overwhelming datasets encompass extensive and complex information from multiple sources like transactions, web interactions, and sensor data. Traditional tools and methods cannot effectively manage and analyze information gleaned from big data within a reasonable timeframe.

Big Data 52

Big Data Media Datasets Unstructured Data 52

Ascend.io

FEBRUARY 28, 2024

While data engineering and Artificial Intelligence (AI) may seem like distinct fields at first glance, their symbiosis is undeniable. The foundation of any AI system is high-quality data. Here lies the critical role of data engineering: preparing and managing data to feed AI models.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

U-Next

MARCH 1, 2023

Introduction Data Engineer is responsible for managing the flow of data to be used to make better business decisions. A solid understanding of relational databases and SQL language is a must-have skill, as an ability to manipulate large amounts of data effectively. How does a data warehouse differ from a database?

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

Knowledge Hut

DECEMBER 26, 2023

According to the Cybercrime Magazine, the global data storage is projected to be 200+ zettabytes (1 zettabyte = 10 12 gigabytes) by 2025, including the data stored on the cloud, personal devices, and public and private IT infrastructures. You can execute this by learning data science with python and working on real projects.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

Rockset

MAY 24, 2019

Remote work affords organizations access to more talent and offers workers greater flexibility in their lives. The Importance of Real-Time Metrics in Managing Distributed Teams FULL employs Amazon Connect for a variety of contact center functions, including telephony services, routing contacts to the right agent, and recording calls.

Management 52

Management Medical SQL Utilities 52

Knowledge Hut

JANUARY 30, 2024

Goal To extract and transform data from its raw form into a structured format for analysis. To uncover hidden knowledge and meaningful patterns in data for decision-making. Data Source Typically starts with unprocessed or poorly structured data sources. Analyzing and deriving valuable insights from data.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

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 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.

Database 72

Database Unstructured Data Data Pipeline Metadata 72

Monte Carlo

JULY 13, 2023

Data-driven organizations generate, collect, and store vast amounts of data. 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. Automating self-service access.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. Structured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Snowflake

APRIL 17, 2023

All features rolled out in public preview in October 2022 are now generally available, including the ability to select specific columns for search optimization; faster searches in VARIANT, ARRAY, OBJECT, and GEOGRAPHY data types; and faster substring searches in string columns. ADD SEARCH OPTIMIZATION ( without the ON clause ).

Food 57

Food Structured Data Utilities Accessible 57

Monte Carlo

FEBRUARY 27, 2024

Right now, RAG is the essential technique to make GenAI models useful by giving an LLM access to an integrated, dynamic dataset while responding to prompts. One note: mastering RAG typically requires implementing a vector database to efficiently manage the queryable data. More on that in a minute, too.

Data Engineering 59

Data Engineering Data Engineer Engineering High Quality Data 59

phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake? Want to learn more about data governance?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Knowledge Hut

MARCH 27, 2024

Think of a database as a smart, organized library that stores and manages information efficiently. On the other hand, data structures are like the tools that help organize and arrange data within a computer program. Table modeling of the data in standard databases facilitates efficient searching and processing.

Database 52

Database Algorithm Relational Database PostgreSQL 52

Cloudera

JUNE 7, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 111

IT Unstructured Data Data Architecture Government 111

Cloudera

DECEMBER 11, 2020

As mentioned in my previous blog on the topic , the recent shift to remote working has seen an increase in conversations around how data is managed. Toolsets and strategies have had to shift to ensure controlled access to data. Driving innovation with secure and governed data .

Data Lake 98

Data Lake Government Data Security Unstructured Data 98

Knowledge Hut

JANUARY 3, 2024

Did you know that almost all database management systems (DBMS) use a particular data organization model? This article provides an introduction to the relational model, which is by far the most common data organization model in DBMS today. In the concept of a relational database management system, data is organized into tables.

MongoDB 52

MongoDB Relational Database Database Accessible 52

Knowledge Hut

NOVEMBER 3, 2023

The need for efficient and agile data management products is higher than ever before, given the ongoing landscape of data science changes. MongoDB is a NoSQL database that’s been making rounds in the data science community. There are several benefits to MongoDB for data science operations.

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 52

Monte Carlo

JUNE 6, 2023

Now, let’s take a closer look at the strengths and weaknesses of the most popular data quality team structures. Data engineering Having the data engineering team lead the response to data quality is by far the most common pattern. It is deployed by about half of all organizations that use a modern data stack.

Data Governance 98

Data Governance Government Data Data Engineering 98

U-Next

FEBRUARY 16, 2023

There is a rapid increase in banking frauds like identity theft, phishing, vishing, smishing, access to debit/credit card details, and UPI/QR code scams. Strategies to Mitigate fraudulent activities : Inculcating an anti-fraud attitude as a way of life is a crucial step in any strategy for managing the risk of fraud.

Banking 74

Banking Systems Education Government 74

Knowledge Hut

DECEMBER 21, 2023

They can make optimum use of data of all kinds, be it real-time or historical, structured or unstructured. Since Hadoop tools make it easy for organizations to deal with massive amounts of data, they can manage the task internally without outsourcing it to external specialists. Hive has high latency.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Towards Data Science

JANUARY 17, 2024

These are key in nearly all data pipelines, allowing for efficient data storage and easier querying and information extraction. They are designed to handle the challenges of big data like size, speed, and structure. Data engineers often face a plethora of choices. Plus, there’s the _delta_log folder.

Big Data 73

Big Data Data Data Storage SQL 73

Data Engineering Podcast

FEBRUARY 3, 2019

In this episode Eric Kansa describes how they process, clean, and normalize the data that they host, the challenges that they face with scaling ETL processes which require domain specific knowledge, and how the information contained in connections that they expose is being used for interesting projects.

Digital Media 100

Digital Media Media PostgreSQL Datasets 100

Knowledge Hut

APRIL 25, 2023

What are Data Engineering Tools? Data engineering tools are software applications that help data engineers manage and process large and complex data sets. Data engineering is a field that requires a range of technical skills, including database management, data modeling, and programming.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Cloudera

JUNE 25, 2021

Many Cloudera customers are making the transition from being completely on-prem to cloud by either backing up their data in the cloud, or running multi-functional analytics on CDP Public cloud in AWS or Azure. The Replication Manager service facilitates both disaster recovery and data migration across different environments.

Cloud 70

Cloud Data Lake Cloud Storage Metadata 70

Precisely

MARCH 9, 2023

A data warehouse implies a certain degree of preprocessing, or at the very least, an organized and well-defined data model. Data lakes, in contrast, are designed as repositories for all kinds of information, which might not initially be organized and structured.

Data Lake 59

Data Lake Data Warehouse Hadoop Raw Data 59

Towards Data Science

JUNE 8, 2023

Now, let’s take a closer look at the strengths and weaknesses of the most popular data quality team structures. Data engineering Photo by Luke Chesser on Unsplash Having the data engineering team lead the response to data quality is by far the most common pattern. Quality falls under their remit as well.

Data Governance 79

Data Governance Government Generalist Data Engineering 79

Data Engineering Weekly

JUNE 4, 2023

Our latest report highlights the impact of bad data on your bottom line (did you know that poor data quality impacts 31% of revenue?!) Access the Report Kaushik Muniandi: Text-Based Search - From Elastic Search to Vector Search Last month or so, I experimented with vector search with embedding.

Data Engineering 52

Data Engineering Data Engineer Engineering Medical 52

Knowledge Hut

MARCH 27, 2024

So long as they have access to a few brief notes, it becomes easy for students to review and go over the fundamental ideas and techniques. An algorithm design cheat sheet is a useful tool for engineers and machine learning specialists to prepare for managing algorithm design chores.

Machine Learning 52

Machine Learning Deep Learning Algorithm Certification 52

Knowledge Hut

JANUARY 19, 2024

What is Data Science Program In our data science program, students gain comprehensive insights into handling diverse data types and statistical information. The curriculum is carefully crafted to impart extensive knowledge about various approaches, skills, methodologies, and tools crucial for managing corporate data effectively.

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Data Science Machine Learning Datasets Algorithm 52