Knowledge Hut

APRIL 23, 2024

Data Warehousing A data warehouse is a centralized repository that stores structured historical data from various sources within an organization. It is designed to support business intelligence (BI) and reporting activities, providing a consolidated and consistent view of enterprise data.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Edureka

AUGUST 27, 2024

Huge volumes of data come from different sources, and processing the data takes time, making it impossible to use all the information for better decision-making. In this blog, let’s explore What AWS Quicksight is and how it disrupts data visualization workflows. What is Amazon Quicksight Used for?

BI 52

BI Business Intelligence AWS Amazon Web Services 52

Knowledge Hut

DECEMBER 26, 2023

Thus, to build a career in Data Science, you need to be familiar with how the business operates, its business model, strategies, problems, and challenges. Data Science Roles As Data Science is a broad field, you will find multiple different roles with different responsibilities.

Data Science 97

Data Science BI Business Intelligence Machine Learning 97

Snowflake

OCTOBER 28, 2024

Here are just a few of the many (89, to be exact) vendors featured in this year’s modern marketing data stack report and event: Analytics & Data Capture Snowplow : Using digital analytics to deliver real-time insights into customer behavior Business Intelligence Domo : Marketing attribution and media mix modeling Sigma : Analyze Google Analytics (..)

Food 80

Food Media Retail Business Intelligence 80

Knowledge Hut

SEPTEMBER 26, 2023

The demand for data professionals with business intelligence skills has increased significantly in recent years. With technological advancements and digital transformations, businesses are taking data very seriously. In today's business environment, data is an invaluable asset.

BI 52

BI Business Intelligence Raw Data Data Analysis 52

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer in the Data Science team is responsible for this sort of data manipulation. Big Data is a part of this umbrella term, which encompasses Data Warehousing and Business Intelligence as well. A Data Engineer's primary responsibility is the construction and upkeep of a data warehouse.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Knowledge Hut

OCTOBER 30, 2023

For any organization to grow, it requires business intelligence reports and data to offer insights to aid in decision-making. This data and reports are generated and developed by Power BI developers. A power BI developer has a crucial role in business management. Ensure compliance with data protection regulations.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

Snowflake

NOVEMBER 2, 2023

For example, customers who need a centralized store of data in large volume and variety – including JSON, text files, documents, images, and video – have built their data lake with Snowflake. Customers that require a hybrid of these to support many different tools and languages have built a data lakehouse.

Data Lake 94

Data Lake Data Warehouse Cloud Unstructured Data 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. Built to make strategic use of data, a Data Warehouse is a combination of technologies and components. 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

Striim

SEPTEMBER 11, 2024

In an ETL-based architecture, data is first extracted from source systems, then transformed into a structured format, and finally loaded into data stores, typically data warehouses. This method is advantageous when dealing with structured data that requires pre-processing before storage.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Striim

OCTOBER 11, 2024

Change Data Capture (CDC) plays a key role here by capturing and streaming only the changes (inserts, updates, deletes) in real time, ensuring efficient data handling and up-to-date information across systems. As a result, stream processing makes real-time business intelligence feasible.

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 52

Knowledge Hut

DECEMBER 26, 2023

Business Intelligence Business Intelligence is an intrinsic element of modern business. By referring to the following books, you will learn about various BI tools and operations like creating reports, tracking performance, managing data sources, etc.

Data Science 52

Data Science Programming Language Scala R (Programming) 52

Monte Carlo

FEBRUARY 15, 2023

A data warehouse is an online analytical processing system that stores vast amounts of data collected within a company’s ecosystem and acts as a single source of truth to enable downstream data consumers to perform business intelligence tasks, machine learning modeling, and more.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Edureka

JULY 16, 2024

Introduction Amazon Redshift, a cloud data warehouse service from Amazon Web Services (AWS), will directly query your structured and semi-structured data with SQL. Amazon Redshift is a petabyte-scale service that allows you to analyze all your data using SQL and your favorite business intelligence (BI) tools.

AWS 40

AWS Data Warehouse Amazon Web Services Business Intelligence 40

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.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 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 Raw Data 52

Monte Carlo

JANUARY 16, 2024

Data issues identified and resolved faster A bright and rapidly evolving future 1. Data lake and data warehouse convergence The data lake vs data warehouse question is constantly evolving. The maxim that data warehouses hold structured data while data lakes hold unstructured data is quickly breaking down.

Data Lake 52

Data Lake Data Warehouse Unstructured Data AWS 52

Knowledge Hut

DECEMBER 26, 2023

However, there has been a lack of Big Data specialists in the IT industry, so if you want to become a Big Data Engineer , now is the time to acquire the required abilities. KnowledgeHut Business Intelligence and Visualization courses  brings you a comprehensive guide to Business Intelligence reporting.

Banking 52

Banking Insurance Finance Cloud Computing 52

AltexSoft

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. Key differences between structured, semi-structured, and unstructured data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

NOVEMBER 10, 2021

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Traditional data warehouse platform architecture. Data lake architecture example. Poor data quality, reliability, and integrity.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

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

ProjectPro

JANUARY 27, 2023

Top ETL Business Use Cases for Streamlining Data Management Data Quality - ETL tools can be used for data cleansing, validation, enriching, and standardization before loading the data into a destination like a data lake or data warehouse.

BI 52

BI ETL Tools Retail Healthcare 52

Knowledge Hut

OCTOBER 24, 2023

SQL and SQL Server BAs must deal with the organization's structured data. BAs can store and process massive volumes of data with the use of these databases. Creation of Reports and Dashboards It is crucial for any business analyst to have a grasp of various kinds of reports and dashboards to accomplish their goals.

Business Analyst 98

Business Analyst Business Intelligence SQL Programming Language 98

Databand.ai

JULY 17, 2023

The main objectives of DataOps include: Collaboration: Facilitating better communication between different teams involved in the data pipeline such as engineers, analysts, scientists, and business stakeholders. However, if machine learning models are at the core of your business operations, MLOps will provide better support.

Data Pipeline 52

Data Pipeline Machine Learning High Quality Data BI 52

Hepta Analytics

FEBRUARY 14, 2022

This means that your data store has to have capabilities of transforming the data. It is mostly used for big data. The data ingestion takes less time compared to ETL. It is also preferred when the use case has more diverse business intelligence. The purpose of the data is not determined.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

Silectis

JANUARY 3, 2021

If you’re new to data engineering or are a practitioner of a related field, such as data science, or business intelligence, we thought it might be helpful to have a handy list of commonly used terms available for you to get up to speed. Big Data Large volumes of structured or unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

phData: Data Engineering

SEPTEMBER 19, 2023

There are tools designed specifically to analyze your data lake files, determine the schema, and allow for SQL statements to be run directly off this data. The Snowflake Data Cloud offers a VARIANT data type that accepts unstructured and semi-structured data into a relational table that can be queried directly.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Knowledge Hut

SEPTEMBER 26, 2023

This integration simplifies data access and management within the Azure cloud environment. Third-Party Integrations: Databricks offers connectors and integrations with popular third-party tools and services, including business intelligence (BI) platforms, data visualization tools, and machine learning frameworks.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Knowledge Hut

JANUARY 22, 2024

Entity sets are used in many database applications, such as data mining, business intelligence, and decision support systems. In each of these applications, entity sets provide a way to structure data and make it easier to understand and work with.

MongoDB 98

MongoDB Database Data Mining Relational Database 98

Edureka

AUGUST 2, 2023

Data integration and transformation: Before analysis, data must frequently be translated into a standard format. Data processing analysts harmonise many data sources for integration into a single data repository by converting the data into a standardised structure.

Data Process 52

Data Process Process Data Cleanse Data Mining 52

U-Next

OCTOBER 25, 2022

What Is Data Manipulation? . In data manipulation, data is organized in a way that makes it easier to read, or that makes it more visually appealing, or that makes it more structured. Data collections can be organized alphabetically to make them easier to understand. . SAS Institute developed this software.

Business Intelligence 40

Business Intelligence Raw Data Data Cleanse Data Analysis 40

Knowledge Hut

MARCH 27, 2024

An organization can make informed decisions based on a big data analytics platform, which works by uncovering patterns, correlations, customer preferences and market trends hidden in the data. Technologies and techniques for data analytics enable organizations to gather new information and analyze data sets on a broad scale.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

Monte Carlo

AUGUST 31, 2023

Data is a priority for your CEO, as it often is for digital-first companies, and she is fluent in the latest and greatest business intelligence tools. What about a frantic email from your CTO about “duplicate data” in a business intelligence dashboard? Rise of the Data Lakehouse Data warehouse or data lake?

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

AltexSoft

AUGUST 4, 2021

Instead of combing through the vast amounts of all organizational data stored in a data warehouse, you can use a data mart — a repository that makes specific pieces of data available quickly to any given business unit. What is a data mart? Initially, DWs dealt with structured data presented in tabular forms.

Data Lake 64

Data Lake Data Warehouse ETL Tools Database 64

AltexSoft

SEPTEMBER 23, 2021

The main purpose of a DW is to enable analytics: It is designed to source raw historical data, apply transformations, and store it in a structured format. This type of storage is a standard part of any business intelligence (BI) system, an analytical interface where users can query data to make business decisions.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Snowflake

JANUARY 23, 2023

A conventional data platform implemented in the cloud is still bound by the same limitations—the complexity of the platform, the need for extraction, transformation, and loading, and an inability to ingest both structured and semi-structured data. Of that group, 75.7%

Data Integration 57

Data Integration Data Data Warehouse Cloud 57