Astera

APRIL 7, 2023

Finally, the stored data is retrieved at optimal speeds to support efficient analysis and decision-making. Essentially, a data warehouse also acts as a centralized database for storing structured, analysis-ready data and giving a holistic view of this data to decision-makers.

Data Warehouse 52

Data Warehouse Healthcare Data Management Data Quality 52

Astera

MARCH 20, 2023

As data warehousing technologies continue to grow in demand , creat ing effective data models has become increasingly important. However, creating an OLTP data model presents various challenges. Well, there’s a hard way of designing and maintaining data models and then there is the Astera’s way.

Data Modelling 52

Data Modelling Data Warehouse Visualization Business Intelligence 52

Astera

DECEMBER 21, 2022

For this reason, most organizations today are creating cloud data warehouse s to get a holistic view of their data and extract key insights quicker. What is a cloud data warehouse? Moreover, when using a legacy data warehouse, you run the risk of issues in multiple areas, from security to compliance.

Data Warehouse 52

Data Warehouse Supply Chain Business Intelligence Business Intelligence 52

The Data Administration Newsletter

APRIL 6, 2021

A metadata-driven data warehouse (MDW) offers a modern approach that is designed to make EDW development much more simplified and faster. It makes use of metadata (data about your data) as its foundation and combines data modeling and ETL functionalities to build data warehouses.

Data Warehouse 52

Data Warehouse Data Modelling Business Intelligence Business Intelligence 52

Astera

MARCH 20, 2023

As data warehousing technologies continue to grow in demand , creat ing effective data models has become increasingly important. However, creating an OLTP data model presents various challenges. Well, there’s a hard way of designing and maintaining data models and then there is the Astera’s way.

Data Modelling 52

Data Modelling Data Warehouse Visualization Business Intelligence 52

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. Building the right data model is an important part of your data strategy.

Data Modelling 84

Data Modelling Big Data Data Analytics Data Analytics 84

Sisense

FEBRUARY 16, 2021

Every aspect of analytics is powered by a data model. A data model presents a “single source of truth” that all analytics queries are based on, from internal reports and insights embedded into applications to the data underlying AI algorithms and much more. Data modeling organizes and transforms data.

Data Modelling 52

Data Modelling Data Warehouse Banking Real-time Data 52

Smart Data Collective

JULY 9, 2023

ETL (Extract, Transform, Load) is a crucial process in the world of data analytics and business intelligence. In this article, we will explore the significance of ETL and how it plays a vital role in enabling effective decision making within businesses. What is ETL? Let’s break down each step: 1.

Data Warehouse 223

Data Warehouse Data Quality Data Analytics Data Analytics 223

Smart Data Collective

JUNE 16, 2022

Online analytical processing is a computer method that enables users to retrieve and query data rapidly and carefully in order to study it from a variety of angles. Trend analysis, financial reporting, and sales forecasting are frequently aided by OLAP business intelligence queries. ( see more ).

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Data Pine

MARCH 31, 2022

4) Business Intelligence Job Roles. Does data excite, inspire, or even amaze you? Do you find computer science and its applications within the business world more than interesting? If you answered yes to any of these questions, you may want to consider a career in business intelligence (BI).In

Business Intelligence 95

Business Intelligence Business Intelligence Data Visualization Visualization 95

ElegantJ BI

JUNE 1, 2022

An integrated solution provides single sign-on access to data sources and data warehouses.’ You can create common data models and BI object templates to publish across tenants with a single click. Integrating augmented analytics within your existing software solutions is simple.

Data Warehouse 130

Data Warehouse Data Modelling Data Architecture Embedded Analytics 130

ElegantJ BI

JUNE 1, 2022

An integrated solution provides single sign-on access to data sources and data warehouses.’ You can create common data models and BI object templates to publish across tenants with a single click. Integrating augmented analytics within your existing software solutions is simple.

Data Warehouse 130

Data Warehouse Data Modelling Data Architecture Embedded Analytics 130

ElegantJ BI

JUNE 1, 2022

An integrated solution provides single sign-on access to data sources and data warehouses.’. The integrated augmented analytics approach includes simple tenant management to deploy with a shared data model for single-tenant mode or an isolated data model for multi-tenant mode and software as a service (SaaS) applications.

Data Warehouse 130

Data Warehouse Data Modelling Data Architecture Embedded Analytics 130

Astera

FEBRUARY 14, 2024

Data vault is an emerging technology that enables transparent, agile, and flexible data architectures, making data-driven organizations always ready for evolving business needs. What is a Data Vault?  A data vault is a data modeling technique that enables you to build data warehouses for enterprise-scale analytics.

Data Warehouse 52

Data Warehouse Data Modelling Agile Data Quality 52

Astera

MAY 25, 2023

Unlocking the Potential of Amazon Redshift Amazon Redshift is a powerful cloud-based data warehouse that enables quick and efficient processing and analysis of big data. Amazon Redshift can handle large volumes of data without sacrificing performance or scalability. What Is Amazon Redshift? 

Data Warehouse 52

Data Warehouse Data Modelling Banking Real-time Data 52

Astera

NOVEMBER 28, 2022

Data warehouses have long served as a single source of truth for data-driven companies. But as data complexity and volumes increase, it’s time to look beyond the traditional data ecosystems. Does that mean it’s the end of data warehousing? Does that mean it’s the end of data warehousing?

Data Warehouse 52

Data Warehouse Data Modelling Data Management Big Data 52

Astera

JULY 3, 2024

This improved data management results in better operational efficiency for organizations, as teams have timely access to accurate data for daily activities and long-term planning. An effective data architecture supports modern tools and platforms, from database management systems to business intelligence and AI applications.

Data Architecture 40

Data Architecture Data Warehouse Data Governance Government 40

Astera

JANUARY 3, 2023

Dimensional modeling is among the most preferred design approaches for building analytics-friendly data warehouses. First introduced in 1996, Kimball ’ s dimension al data models have now bec o me cornerstones of modern data warehouse design and development. Dimensional Data Model.

Data Warehouse 52

Data Warehouse Data Modelling Business Intelligence Business Intelligence 52

Astera

SEPTEMBER 1, 2023

The significance of data warehousing for insurance cannot be overstated. It forms the bedrock of modern insurance operations, facilitating data-driven insights and streamlined processes to better serve policyholders. The data warehouse has the highest adoption of data solutions, used by 54% of organizations.

Data Warehouse 40

Data Warehouse Data Modelling Data Quality Data Security 40

Astera

JANUARY 25, 2024

Reverse ETL (Extract, Transform, Load) is the process of moving data from central data warehouse to operational and analytic tools. How Does Reverse ETL Fit in Your Data Infrastructure Reverse ETL helps bridge the gap between central data warehouse and operational applications and systems.

E-Commerce 52

E-Commerce Data Warehouse Retail Customer Experience 52

Astera

MARCH 7, 2024

ETL testing is a set of procedures used to evaluate and validate the data integration process in a data warehouse environment. In other words, it’s a way to verify that the data from your source systems is extracted, transformed, and loaded into the target storage as required by your business rules.

Data Warehouse 52

Data Warehouse Data Quality Documentation Data Modelling 52

Insight Software

JULY 31, 2023

Financial and operational reporting teams may need to rely on IT personnel for report customization, data modeling, or resolving technical issues. That’s where we use the analytics side of Angles, when we’re able to do multiple loads throughout the day and pull that data out of EBS into our data warehouse.

Data Warehouse 52

Data Warehouse Real-time Data Finance Data Modelling 52

Astera

JANUARY 23, 2024

Businesses need scalable, agile, and accurate data to derive business intelligence (BI) and make informed decisions. Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. What are Information Marts?

Agile 52

Agile Data Warehouse Data Quality Government 52

Astera

APRIL 27, 2023

This is where data extraction tools from companies like Matillion, Astera , and Fivetran are used to organize and prepare data for a cloud data warehouse. ELT or ETL tools , such as DBT, work within a cloud data warehouse to convert, clean, and structure data, into a format usable by data engineers and analysts.

Data Warehouse 52

Data Warehouse Big Data Data Analytics Data Analytics 52

Sisense

JANUARY 15, 2021

Access to information can be a game-changer for businesses looking to unlock strategic advantages through analytical insights. Ensuring that your organization has the right business intelligence and analytics tools to drive this innovation is key. It’s no secret that data teams are becoming indispensable to organizations.

Skillset 75

Skillset Data Warehouse Data Modelling Business Intelligence 75

Astera

DECEMBER 14, 2022

Kimball-style dimensional modeling has been the go-to architecture for most data warehouse developers over the past couple of decades. The questions that arise, however, are the following: How easy is it to load and maintain data in fact and dimension tables? And Is it worth the effort?

Data Warehouse 52

Data Warehouse Data Modelling Business Intelligence Business Intelligence 52

Astera

SEPTEMBER 20, 2024

his setup allows users to access and manage their data remotely, using a range of tools and applications provided by the cloud service. Cloud databases come in various forms, including relational databases, NoSQL databases, and data warehouses. There are several types of NoSQL databases, including document stores (e.g.,

Data Warehouse 40

Data Warehouse Cloud Computing E-Commerce Documentation 40

The Data Administration Newsletter

APRIL 19, 2022

Introduction We are living in the age of a data revolution, and more corporations are realizing that to lead—or in some cases, to survive—they need to harness their data wealth effectively.

Data Warehouse 72

Data Warehouse Data Modelling Business Intelligence Business Intelligence 72

Astera

JUNE 14, 2023

These transactions typically involve inserting, updating, or deleting small amounts of data. Normalized data structure: OLTP databases have a normalized data structure. This means that they use a data model that minimizes redundancy and ensures data consistency. through a built-in OData service.

Supply Chain 40

Supply Chain Data Warehouse Financial Analysis Real-time Data 40

Tableau

DECEMBER 7, 2022

Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments. Cut costs by consolidating data warehouse investments.

Talent Acquisition 98

Talent Acquisition Data Warehouse Data Architecture Visualization 98

Tableau

DECEMBER 7, 2022

Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments. Cut costs by consolidating data warehouse investments.

Talent Acquisition 98

Talent Acquisition Data Warehouse Data Architecture Visualization 98

Astera

JANUARY 2, 2024

Businesses, both large and small, find themselves navigating a sea of information, often using unhealthy data for business intelligence (BI) and analytics. Relying on this data to power business decisions is like setting sail without a map. This is why organizations have effective data management in place.

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 52

Astera

JULY 13, 2023

This process includes moving data from its original locations, transforming and cleaning it as needed, and storing it in a central repository. Data integration can be challenging because data can come from a variety of sources, such as different databases, spreadsheets, and data warehouses.

Data Warehouse 40

Data Warehouse Data Quality Data Governance Master Data Management 40

Sisense

AUGUST 22, 2019

SQL is a critical skill for business intelligence. From accessing to transforming to reporting on data, SQL gives you the power to get the job done. These are the types of questions that take a customer to the next level of business intelligence — predictive analytics. . Python, R, and Analytics. A New Paradigm.

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Predictive Analytics Data Warehouse Business Intelligence Business Intelligence 73

Astera

JUNE 3, 2024

Data warehouses Data warehouses are a specialized type of database designed for a specific purpose: large-scale data analysis. Today, cloud computing, artificial intelligence (AI), and machine learning (ML) are pushing the boundaries of databases. These are some of the most common databases.

Data Warehouse 52

Data Warehouse Documentation E-Commerce Data Management 52

Sisense

MARCH 14, 2021

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly. displaying BI insights for human users).

Big Data 52

Big Data Supply Chain Data Analytics Data Analytics 52

Astera

JANUARY 31, 2024

Its extensibility is evident through components, such as SQL Server Integration Services (SSIS) for ETL , SQL Server Reporting Services (SSRS) for creating and managing reports, SQL Server Analysis Service (SSAS) for analytical data models, and so on. Azure SQL Database).

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Data Warehouse Visualization Data Management Data Quality 52