Overview of Fraud Detection using Machine learningFraud detection using machine learning has emerged as a powerful and effective approach to identifying and preventing fraudulent activities across various domains. With the increasing complexity of fraudulent schemes and the sheer volume of data generated in today's digital world, traditional rule-based methods have be
Relational DatabasesThe relational database is a database management system (DBMS) that organizes and stores data in a tabular format consisting of rows and columns. In a relational database, data is structured into tables representing a specific entity or concept. Each row in the table represents a unique record, and each column represents a data attribute or field a
Data Analysis Vs. Data EngineeringData analysis and data engineering are distinct but interconnected fields in data science and analytics. Both play crucial roles in making sense of data and extracting valuable insights, but they have different focuses and responsibilities. Let's explore data analysis vs. data engineering:What is Data analysis?In Data analysis, we exa
Data Science in RetailData is an important factor in any business sector nowadays. Data plays a crucial role in the decision-making process of businesses to drive growth. We live in an age where data science is revolutionizing various industries—one of the main industries getting affected due to the application of data science in retail sector.Many e-commerce and r
Data Conversion ProcessThe digital era is not a future forecast. We are already in the middle of the digital age, where data is crucial. Data management has become an important part of business processes. Businesses use different business tools and systems to use gathered data for analysis. The collected data don't need to be ready for use. Very firstly, data enginee
dbt (Data Build Tool) DBT (Data Build Tool) - an open-source tool for orchestrating data transformations in your data warehouse. It allows you to define and manage your data transformation workflows, making building and maintaining reliable data pipelines easier. Let us learn the general steps of data transformation with dbt. Data Transformation wi
How to build a data pipeline? Building a data pipeline involves extracting, transforming, & loading (ETL) data from various sources into a target destination. Let us learn how to build a data pipeline? Here's a general framework for building a data pipeline:Define Objectives:Clearly define the objectives and requirements to build a data pipeline. Ident
On-premise systems have many advantages but also have a huge share of challenges—for example, system maintenance, licensing, and software upgrades. Most businesses are moving to cloud-based platforms to eliminate their challenges in on-premice systems. There are also challenges in moving to cloud technology. Snowflake is one of the top-most preferred cloud data wa
Enterprise Data Lake Engineering ServicesEnterprise data lake engineering services refer to specialized services offered to organizations to design, build, and maintain data lakes. A data lake is a centralized repository that stores structured, semi-structured, and unstructured data in its raw format.It is a scalable and cost-effective solution for storing vast amount
What is Data Engineering?Data engineering is a field of study and practice that focuses on designing, developing, and managing data pipelines and infrastructure. It involves collecting, ingestion, transforming, and storing data in a manner that enables efficient and effective analysis and processing. Data engineers work with various tools and technologies, and program
