Dataconomy

MARCH 24, 2023

In today’s fast-paced business landscape, companies need to stay ahead of the curve to remain competitive. Business intelligence (BI) has emerged as a key solution to help companies gain insights into their operations and market trends. What is business intelligence?

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Dataconomy

MARCH 24, 2023

In today’s fast-paced business landscape, companies need to stay ahead of the curve to remain competitive. Business intelligence (BI) has emerged as a key solution to help companies gain insights into their operations and market trends. What is business intelligence?

Business Intelligence 70

Business Intelligence Business Intelligence Data Analysis Data Analysis 70

Data Science Blog

MAY 15, 2023

tl;dr Ein Data Lakehouse ist eine moderne Datenarchitektur, die die Vorteile eines Data Lake und eines Data Warehouse kombiniert. Organisationen können je nach ihren spezifischen Bedürfnissen und Anforderungen zwischen einem Data Warehouse und einem Data Lakehouse wählen.

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Data Warehouse Data Lakes Azure AWS 147

Smart Data Collective

JULY 22, 2019

Big or small, every business needs good tools to analyze data and develop the most suitable business strategy based on the information they get. Business intelligence tools are means that help companies get insights from their data and get a better understanding of what directions and trends to follow.

Business Intelligence 80

Business Intelligence Business Intelligence Power BI Tableau 80

Data Science Dojo

SEPTEMBER 11, 2024

These experiences facilitate professionals from ingesting data from different sources into a unified environment and pipelining the ingestion, transformation, and processing of data to developing predictive models and analyzing the data by visualization in interactive BI reports.

Power BI 195

Power BI Data Pipeline Data Warehouse Data Engineering 195

ODSC - Open Data Science

SEPTEMBER 27, 2023

In this article, we will delve into the concept of data lakes, explore their differences from data warehouses and relational databases, and discuss the significance of data version control in the context of large-scale data management. Schema Enforcement: Data warehouses use a “schema-on-write” approach.

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

Smart Data Collective

APRIL 8, 2020

Dating back to the 1970s, the data warehousing market emerged when computer scientist Bill Inmon first coined the term ‘data warehouse’. Created as on-premise servers, the early data warehouses were built to perform on just a gigabyte scale. Cloud based solutions are the future of the data warehousing market.

Data Warehouse 134

Data Warehouse Big Data Big Data Business Intelligence 134

Tableau

JUNE 8, 2021

Domain experts, for example, feel they are still overly reliant on core IT to access the data assets they need to make effective business decisions. In all of these conversations there is a sense of inertia: Data warehouses and data lakes feel cumbersome and data pipelines just aren't agile enough.

Tableau 101

Tableau Data Lakes Data Warehouse SQL 101

ODSC - Open Data Science

JUNE 12, 2023

They all agree that a Datamart is a subject-oriented subset of a data warehouse focusing on a particular business unit, department, subject area, or business functionality. The Datamart’s data is usually stored in databases containing a moving frame required for data analysis, not the full history of data.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

Data Science Blog

SEPTEMBER 3, 2024

Dabei arbeiten wir technologie-offen und mit nahezu allen Tools – Und oft in enger Verbindung mit Initiativen der Business Intelligence und Data Science. für SAP oder Oracle ERP an, mit vordefinierten Event Log SQL Skripten für viele Standard-Prozesse, insbesondere Procure-to-Pay und Order-to-Cash.

Data Science 130

Data Science Power BI Azure Data Warehouse 130

Mlearning.ai

FEBRUARY 16, 2023

Today, companies are facing a continual need to store tremendous volumes of data. The demand for information repositories enabling business intelligence and analytics is growing exponentially, giving birth to cloud solutions. Snowflake data warehouses deliver greater capacity without the need for any additional equipment.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

Pickl AI

JULY 3, 2023

What is Business Intelligence? Business Intelligence (BI) refers to the technology, techniques, and practises that are used to gather, evaluate, and present information about an organisation in order to assist decision-making and generate effective administrative action. billion in 2015 and reached around $26.50

Business Intelligence 52

Business Intelligence Business Intelligence SQL Data Visualization 52

IBM Journey to AI blog

MAY 9, 2023

Watsonx.data will allow users to access their data through a single point of entry and run multiple fit-for-purpose query engines across IT environments. Through workload optimization an organization can reduce data warehouse costs by up to 50 percent by augmenting with this solution. [1]

Data Warehouse 98

Data Warehouse AWS AI AI 98

Alation

JANUARY 17, 2023

It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Data orchestration tools. Business intelligence (BI) platforms. Better Data Culture.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

Tableau

JUNE 8, 2021

Domain experts, for example, feel they are still overly reliant on core IT to access the data assets they need to make effective business decisions. In all of these conversations there is a sense of inertia: Data warehouses and data lakes feel cumbersome and data pipelines just aren't agile enough.

Tableau 52

Tableau Data Lakes Data Warehouse SQL 52

phData

MAY 14, 2024

They will focus on organizing data for quicker queries, optimizing virtual data warehouses, and refining query processes. The result is a data warehouse offering faster query responses, improved performance, and cost efficiency throughout your Snowflake account.

SQL 52

SQL Data Warehouse Data Engineering Data Engineer 52

phData

SEPTEMBER 19, 2023

A rigid data model such as Kimball or Data Vault would ruin this flexibility and essentially transform your data lake into a data warehouse. However, some flexible data modeling techniques can be used to allow for some organization while maintaining the ease of new data additions.

Data Lakes 52

Data Lakes Data Modeling Data Models Data Warehouse 52

Smart Data Collective

SEPTEMBER 8, 2021

The ETL process is defined as the movement of data from its source to destination storage (typically a Data Warehouse) for future use in reports and analyzes. The data is initially extracted from a vast array of sources before transforming and converting it to a specific format based on business requirements.

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ETL Hadoop Data Warehouse Data Pipeline 97

Dataconomy

SEPTEMBER 27, 2023

The Microsoft Certified Solutions Associate and Microsoft Certified Solutions Expert certifications cover a wide range of topics related to Microsoft’s technology suite, including Windows operating systems, Azure cloud computing, Office productivity software, Visual Studio programming tools, and SQL Server databases.

Database Administration 113

Database Administration Database Azure Cloud Computing 113

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation.

Data Warehouse 87

Data Warehouse Azure SQL ETL 87

IBM Journey to AI blog

JULY 11, 2023

Data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics that enable faster decision making and insights.

Data Warehouse 72

Data Warehouse Database Cloud Data Business Intelligence 72

ODSC - Open Data Science

FEBRUARY 24, 2023

With Great Expectations , data teams can express what they “expect” from their data using simple assertions. Great Expectations provides support for different data backends such as flat file formats, SQL databases, Pandas dataframes and Sparks, and comes with built-in notification and data documentation functionality.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

IBM Journey to AI blog

SEPTEMBER 11, 2023

Codd published his famous paper “ A Relational Model of Data for Large Shared Data Banks.” Boyce to create Structured Query Language (SQL). Thus, was born a single database and the relational model for transactions and business intelligence. ” His paper and research went on to inspire Donald D.

Database 105

Database SQL Data Warehouse Machine Learning 105

Smart Data Collective

JUNE 16, 2022

There are a lot of important queries that you need to run as a data scientist. This tool can be great for handing SQL queries and other data queries. Every data scientist needs to understand the benefits that this technology offers. The data is processed and modified after it has been extracted. see more ).

Analytics 131

Analytics Analytics Data Scientist Data Warehouse 131

Pickl AI

AUGUST 9, 2024

Real-world examples illustrate their application, while tools and technologies facilitate effective hierarchical data management in various industries. Retail Industry In a retail data warehouse , hierarchies can be used to organise product categories.

Data Warehouse 52

Data Warehouse Data Quality ETL Business Intelligence 52

IBM Journey to AI blog

JULY 3, 2024

This includes integration with your data warehouse engines, which now must balance real-time data processing and decision-making with cost-effective object storage, open source technologies and a shared metadata layer to share data seamlessly with your data lakehouse.

AI 45

AI AI Data Quality Database 45

IBM Journey to AI blog

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

IBM Journey to AI blog

APRIL 8, 2024

Answer : Along with standard RDS features, Amazon RDS for Db2 supports key Db2 features, such as row and column organized tables for mixed and analytic workloads, the Adaptive Workload Optimizer to for better resource management, and rules-based access controls for advanced data protection.   Scalability 5.

AWS 91

AWS Database Data Warehouse Analytics 91

Alation

MARCH 31, 2022

In the breakneck world of data, which I have been privy to since the mid 1990s, business intelligence remains one of the most enduring terms. The writer Richard Millar Devens used “business intelligence” to describe how a banker had the foresight to gather and act on information thus getting the jump on his competition.

Business Intelligence 52

Business Intelligence Business Intelligence Data Warehouse Data Scientist 52

Pickl AI

AUGUST 11, 2024

These examples highlight how fact tables are structured to capture essential business metrics and facilitate insightful analysis, driving informed decision-making across different contexts. These tools are essential for populating fact tables with accurate and timely data.

Data Quality 52

Data Quality Data Warehouse Data Governance Business Intelligence 52

IBM Journey to AI blog

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases.

Data Quality 52

Data Quality Data Lakes Data Warehouse Business Intelligence 52

ODSC - Open Data Science

FEBRUARY 8, 2023

Common databases appear unable to cope with the immense increase in data volumes. This is where the BigQuery data warehouse comes into play. BigQuery operation principles Business intelligence projects presume collecting information from different sources into one database. You only pay for the resources you use.

Database 97

Database Business Intelligence Business Intelligence Big Data 97

Alation

FEBRUARY 7, 2023

It wouldn’t be until 2013 that the topic of data lineage would surface again – this time while working on a data warehouse project. Data warehouses obfuscate data’s origin In 2013, I was a Business Intelligence Engineer at a financial services company.

Data Warehouse 52

Data Warehouse ETL Business Intelligence Business Intelligence 52

Pickl AI

APRIL 26, 2024

This comprehensive blog outlines vital aspects of Data Analyst interviews, offering insights into technical, behavioural, and industry-specific questions. It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Pickl AI

AUGUST 1, 2023

The primary goal of Data Engineering is to transform raw data into a structured and usable format that can be easily accessed, analyzed, and interpreted by Data Scientists, analysts, and other stakeholders. Future of Data Engineering The Data Engineering market will expand from $18.2

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

AWS Machine Learning Blog

DECEMBER 29, 2022

Many of the RStudio on SageMaker users are also users of Amazon Redshift , a fully managed, petabyte-scale, massively parallel data warehouse for data storage and analytical workloads. It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools.

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AWS Machine Learning Blog

OCTOBER 9, 2024

To start using CloudWatch anomaly detection, you first must ingest data into CloudWatch and then enable anomaly detection on the log group. Using Amazon Redshift ML for anomaly detection Amazon Redshift ML makes it easy to create, train, and apply machine learning models using familiar SQL commands in Amazon Redshift data warehouses.

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AWS ML ML Data Quality 90