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

Hepta Analytics

FEBRUARY 14, 2022

The data ingestion takes less time compared to ETL. It is also preferred when the use case has more diverse business intelligence. When the business intelligence needs change, they can go query the raw data again. ELT: source Data Lake vs Data Warehouse Data lake stores raw data.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

Knowledge Hut

JANUARY 19, 2024

Business Intelligence Transforming raw data into actionable insights for informed business decisions. This subject equips you with skills in handling various BI (Business Intelligence) methods and tools. Coding Coding is the wizardry behind turning data into insights.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

Ascend.io

AUGUST 31, 2023

The Data Warehouse Pattern The heart of a data warehouse lies in its schema, capturing intricate details of business operations. This unchanging schema forms the foundation for all queries and business intelligence. Modern platforms like Redshift , Snowflake , and BigQuery have elevated the data warehouse model.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

ProjectPro

DECEMBER 7, 2021

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 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

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

ProjectPro

JULY 22, 2016

Data warehouses do a good job for what they are meant to do, but with disparate data sources and different data types like transaction logs, social media data, tweets, user reviews, and clickstream data –Data Lakes fulfil a critical need. Data Warehouses do not retain all data whereas Data Lakes do.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

Knowledge Hut

DECEMBER 26, 2023

Let us first get a clear understanding of why Data Science is important. What is the need for Data Science? If we look at history, the data that was generated earlier was primarily structured and small in its outlook. A simple usage of Business Intelligence (BI) would be enough to analyze such datasets.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Edureka

AUGUST 2, 2023

Organisations and businesses are flooded with enormous amounts of data in the digital era. Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly. Data processing analysts can be useful in this situation.

Data Process 52

Data Process Process Data Cleanse Data Mining 52

ProjectPro

MAY 20, 2015

Fred Shilmover, CEO of InsightSquared says- "It's an exciting time to be in the big data analytics space pointing to recent developments such as Tableau Software's highly successful IPO and a $125 million funding round for Domo. Palantir Metropolis- This product focusses on information management, data integration and quantitative analytics.

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

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

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

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

Knowledge Hut

MARCH 27, 2024

The collection of meaningful market data has become a critical component of maintaining consistency in businesses today. A company can make the right decision by organizing a massive amount of raw data with the right data analytic tool and a professional data analyst.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 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. They need to be transformed.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 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. Data integration , on the other hand, happens later in the data management flow.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 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

JANUARY 18, 2024

However, while anyone may access raw data, you can extract relevant and reliable information from the numbers that will determine whether or not you can achieve a competitive edge for your company. When people speak about insights in data science, they generally mean one of three components: What is Data?

Data Science 52

Data Science Media Food Data 52

ProjectPro

JANUARY 27, 2023

You have probably heard the saying, "data is the new oil". It is extremely important for businesses to process data correctly since the volume and complexity of raw data are rapidly growing. Business Intelligence - ETL is a key component of BI systems for extracting and preparing data for analytics.

BI 52

BI ETL Tools Retail Healthcare 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. Another type of data storage — a data lake — tried to address these and other issues.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Edureka

JUNE 1, 2023

Data Analytics tools and technologies offer opportunities and challenges for analyzing data efficiently so you can better understand customer preferences, gain a competitive advantage in the marketplace, and grow your business. What is Data Analytics?

AWS 52

AWS Data Analytics Cloud Amazon Web Services 52

Monte Carlo

JUNE 14, 2023

Data transformation dbt – Short for data build tool, is the open source leader for transforming data once it’s loaded into your warehouse. Dataform – Now part of the Google Cloud , Dataform allows you to transform raw data from your warehouse into something usable by BI and analytics tools.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

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

ProjectPro

JANUARY 31, 2022

This is the reason why we need Data Warehouses. What is Snowflake Data Warehouse? A Data Warehouse is a central information repository that enables Data Analytics and Business Intelligence (BI) activities. Use Cases SQL-based business intelligence use cases are the best fit for Snowflake.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

ProjectPro

AUGUST 24, 2021

Within no time, most of them are either data scientists already or have set a clear goal to become one. Nevertheless, that is not the only job in the data world. And, out of these professions, this blog will discuss the data engineering job role. Google BigQuery receives the structured data from workers.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

AUGUST 18, 2021

Ace your next data analyst interview with these Tableau interview questions and answers that cover all the important topics and concepts in Tableau. Tableau is one of the most significant data visualization and business intelligence tools used by organizations across industries. What are the important topics in Tableau?

BI 40

BI Database-centric SQL Software Engineer 40

AltexSoft

MAY 14, 2021

A single car connected to the Internet with a telematics device plugged in generates and transmits 25 gigabytes of data hourly at a near-constant velocity. And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. Data storage and processing.

Big Data 78

Big Data Data Analytics IT NoSQL 78

AltexSoft

JULY 29, 2022

According to the study by the Business Application Research Center (BARC), Hadoop found intensive use as. a suitable technology to implement data lake architecture. Snowflake: an evolving ecosystem for all types of data.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

JANUARY 31, 2023

Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data. Big data enables businesses to gain a deeper understanding of their industry and helps them extract valuable information from the unstructured and raw data that is regularly collected.

Big Data 52

Big Data Hadoop AWS Relational Database 52

AltexSoft

SEPTEMBER 10, 2021

So, why does anyone need to integrate data in the first place? Today, companies want their business decisions to be driven by data. But here’s the thing — information required for business intelligence (BI) and analytics processes often lives in a breadth of databases and applications.

Data Integration 52

Data Integration Data Consolidation Data Warehouse BI 52

ProjectPro

JULY 27, 2021

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

MARCH 14, 2023

Data storage The tools mentioned in the previous section are instrumental in moving data to a centralized location for storage, usually, a cloud data warehouse, although data lakes are also a popular option. But this distinction has been blurred with the era of cloud data warehouses.

IT 59

IT Data Warehouse Data Governance Data Lake 59

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Google Cloud 64