Analytics Vidhya

FEBRUARY 2, 2023

Introduction SQL injection is an attack in which a malicious user can insert arbitrary SQL code into a web application’s query, allowing them to gain unauthorized access to a database. We can use this to steal sensitive information or make unauthorized changes to the data stored in the database.

Database 204

Database SQL Coding Accessible 204

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

FEBRUARY 29, 2024

A database is a structured data collection that is stored and accessed electronically. According to a database model, the organization of data is known as database design. While using Amazon SageMaker datasets are quick to access and load. You can find the image dataset, time-series dataset, reviews, etc.

Data Science 98

Data Science Datasets Database Design Machine Learning 98

ThoughtSpot

MARCH 5, 2024

Create Snowflake dynamic tables In Snowflake, create dynamic tables by writing SQL queries that define how data should be transformed and materialized. Grant ThoughtSpot access In Snowflake, grant the ThoughtSpot service account USAGE privileges on the schemas containing the dynamic tables. Set refresh schedules as needed.

BI 94

BI Datasets Raw Data SQL 94

Knowledge Hut

APRIL 23, 2024

This guide will help you comprehend big data 4 characteristics to understand all the containing Vs! Volume: Quantity vs Accessibility Volume is the first of the four V's in big data and pertains to the size or magnitude of data being generated, collected, and stored. Customer data come in numerous formats.

Big Data 52

Big Data Media Datasets Unstructured Data 52

U-Next

MARCH 1, 2023

They are also responsible for ensuring that the data is clean and organized, as well as making sure that it’s easily accessible to other departments within the company. They often work closely with database administrators to ensure they have access to all of the tools and resources needed to meet their goals.

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

Data Engineering Weekly

APRIL 7, 2024

link] Spotify: Data Platform Explained In the ever-evolving landscape of data-driven decision-making, a well-structured data platform emerges as a critical asset.

Data Engineering 70

Data Engineering Data Engineer Engineering Unstructured Data 70

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

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

Ascend.io

FEBRUARY 28, 2024

Read More: AI Data Platform: Key Requirements for Fueling AI Initiatives How Data Engineering Enables AI Data engineering is the backbone of AI’s potential to transform industries , offering the essential infrastructure that powers AI algorithms.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 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

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

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 55

Food Structured Data Utilities Accessible 55

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

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 90

Machine Learning Unstructured Data Data Analytics Government 90

Cloudera

JUNE 3, 2022

When it comes to the early stages in the data science process, data scientists often find themselves jumping between a wide range of tooling. First of all, there’s the question of what data is currently available within their organization, where it is, and how it can be accessed. Next Steps.

Data Analysis 88

Data Analysis PostgreSQL Data Science SQL 88

AltexSoft

AUGUST 29, 2023

Data sources can be broadly classified into three categories. Structured data sources. These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined. Semi-structured data sources. Raw data store section.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Snowflake

JULY 10, 2023

With this new Snowpark capability, data engineers and data scientists can process any type of file directly in Snowflake, regardless if files are stored in Snowflake-managed storage or externally. Mike Tuck, Air Pollution Specialist Why unstructured data?

Unstructured Data 40

Unstructured Data Python Process Scala 40

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. They clean, cumulate, connect and structure data for analysis-based applications.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

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

Knowledge Hut

NOVEMBER 3, 2023

MongoDB is used for data science, meaning that we utilize the capabilities of this NoSQL database system as part of our data analysis and data modeling processes, which fall under the realm of data science. There are several benefits to MongoDB for data science operations.

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 52

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. It established a data governance framework within its enterprise data lake.

Data Lake 98

Data Lake Government Data Security Unstructured Data 98

phData: Data Engineering

SEPTEMBER 19, 2023

Cost reduction by minimizing data redundancy, improving data storage efficiency, and reducing the risk of errors and data-related issues. Data Governance and Security By defining data models, organizations can establish policies, access controls, and security measures to protect sensitive data.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

ProjectPro

FEBRUARY 16, 2023

Data integration with ETL has evolved from structured data stores with high computing costs to natural state storage with read operation alterations thanks to the agility of the cloud. Data integration with ETL has changed in the last three decades. This ensures that companies' data is always protected and secure.

AWS 52

AWS Data Management ETL Tools Management 52

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. These databases are not just a trend, but a fundamental shift in how data is managed, accessed, and utilized in real-time AI applications.

Data Engineering 59

Data Engineering Data Engineer Engineering High Quality 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 82

Data Governance Government Generalist Data Engineering 82

Cloudera

SEPTEMBER 29, 2021

Among governments’ priorities are encouraging digital adoption, facilitating access and usage of relevant government services alongside enabling more digital transactions. Through processing vast amounts of structured and semi-structured data, AI and machine learning enabled effective fraud prevention in real-time on a national scale. .

Medical 78

Medical Government Hospitality Electronics 78

Cloudera

SEPTEMBER 17, 2020

By enabling their event analysts to monitor and analyze events in real time, as well as directly in their data visualization tool, and also rate and give feedback to the system interactively, they increased their data to insight productivity by a factor of 10. . Our solution: Cloudera Data Visualization.

Unstructured Data 80

Unstructured Data Pharmaceutical Data Warehouse MySQL 80

Knowledge Hut

JANUARY 3, 2024

Users can easily access data and run queries without needing to understand complex concepts. The relational model also supports collaboration by allowing multiple users to access and update the same data. Finally, the relational model offers security features that protect data from unauthorized access and modification.

MongoDB 52

MongoDB Relational Database Database Accessible 52

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

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. Many firms’ internal networking can now be accessible thanks to our accounts’ accessibility, data in the cloud, and portable devices.

Banking 74

Banking Systems Education Government 74

Knowledge Hut

JANUARY 19, 2024

The syllabus, resembling a guidebook, talks about organized storage, a unified view, and the flexibility offered by data lakes. For beginners in the curriculum for self-study, this is about creating a scalable and accessible data hub. Importance: Efficient organization and retrieval of data.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

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

These are the situations where having a lot of data stored in one location and being able to access it quickly are necessary. What is a Data Structure? Using a data structure allows you to efficiently arrange data on a computer. Supports complex query relationships and ensures data integrity.

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 106

IT Unstructured Data Data Architecture Government 106

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. Because of its complete accessibility, user-friendliness, and strong community support, Python is the most popular programming language among aficionados for machine learning.

Machine Learning 52

Machine Learning Deep Learning Algorithm Certification 52