Astera

NOVEMBER 14, 2023

If you have had a discussion with a data engineer or architect on building an agile data warehouse design or maintaining a data warehouse architecture, you’d probably hear them say that it is a continuous process and doesn’t really have a definite end. What do you need to build an agile data warehouse?

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Astera

DECEMBER 22, 2022

Enterprises will soon be responsible for creating and managing 60% of the global data. Traditional data warehouse architectures struggle to keep up with the ever-evolving data requirements, so enterprises are adopting a more sustainable approach to data warehousing. Best Practices to Build Your Data Warehouse .

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Astera

OCTOBER 27, 2023

What is a Cloud Data Warehouse? Simply put, a cloud data warehouse is a data warehouse that exists in the cloud environment, capable of combining exabytes of data from multiple sources. A cloud data warehouse is critical to make quick, data-driven decisions.

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Domo

DECEMBER 9, 2020

That’s the challenge faced by organizations that are already heavily invested in data lakes and warehouses, or are in highly regulated industries—like healthcare or finance—that require their data be kept in their infrastructure at rest for security or compliance reasons. The benefits of data federation. The solution?

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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.

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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.

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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.

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Astera

APRIL 27, 2023

Data Lake Vs Data Warehouse Every business needs to store, analyze, and make decisions based on data. To do this, they must choose between two popular data storage technologies: data lakes and data warehouses. What is a Data Lake? What is a Data Warehouse?

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Astera

NOVEMBER 17, 2022

Most enterprises out there rely on a data warehouse as a single source of truth — a consolidated data repository that serves as a reporting layer for companies to identify trends and gain valuable business insights. If you want to explore the agile way to build your data warehouse, reach us at sales@astera.com today.

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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

Data and analytics are indispensable for businesses to stay competitive in the market. Hence, it’s critical for you to look into how cloud data warehouse tools can help you improve your system. According to Mordor Intelligence , the demand for data warehouse solutions will reach $13.32 billion by 2026. Ease of Use.

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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.

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Data Warehouse Supply Chain Business Intelligence Business Intelligence 52

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.

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Data Modelling Data Warehouse Banking Real-time Data 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.

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Smart Data Collective

MAY 16, 2022

These include, but are not limited to, database management systems, data mining software, decision support systems, knowledge management systems, data warehousing, and enterprise data warehouses. Some data management strategies are in-house and others are outsourced. They are a part of the data management system.

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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.

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Astera

FEBRUARY 27, 2024

52% of IT experts consider faster analytics essential to data warehouse success. However, scaling your data warehouse and optimizing performance becomes more difficult as data volume grows. Leveraging data warehouse best practices can help you design, build, and manage data warehouses more effectively.

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Astera

FEBRUARY 27, 2024

52% of IT experts consider faster analytics essential to data warehouse success. However, scaling your data warehouse and optimizing performance becomes more difficult as data volume grows. Leveraging data warehouse best practices can help you design, build, and manage data warehouses more effectively.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

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.

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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.

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Astera

JANUARY 11, 2023

The primary purpose of your data warehouse is to serve as a centralized repository for historical data that can be quickly queried for BI reporting and analysis. Data modeling — which defines the database schema — is the heart of your data warehouse . Develop and deploy high-volume data warehouses.

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Astera

JANUARY 11, 2023

The primary purpose of your data warehouse is to serve as a centralized repository for historical data that can be quickly queried for BI reporting and analysis. Data modeling — which defines the database schema — is the heart of your data warehouse . Data Model Verification.

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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? 

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Astera

FEBRUARY 28, 2023

Dimensional modelling is still the most reliable modeling approach for designing a data warehouse for reporting use cases. Its denormalized structure significantly improves query performance, allowing for fast and seamless data consumption and reporting. But more on SCDs in a bit.

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BizAcuity

APRIL 1, 2023

Teradata is based on a parallel Data Warehouse with shared-nothing architecture. Data is stored in a row-based format. It supports a hybrid storage model in which frequently accessed data is stored in SSD whereas rarely accessed data is stored on HDD. The BYNET interconnect supports up to 512 nodes.

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BizAcuity

SEPTEMBER 22, 2022

Teradata is based on a parallel Data Warehouse with shared-nothing architecture. Data is stored in a row-based format. It supports a hybrid storage model in which frequently accessed data is stored in SSD whereas rarely accessed data is stored on HDD. Not being an agile cloud data warehouse.

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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?

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Data Warehouse Data Modelling Data Management Data Automation 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.

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ElegantJ BI

MARCH 16, 2022

There are many benefits to Embedded BI approach including: World-Class Data Architecture provides access to a wealth of data sources and data warehouses, and accommodates business application architecture with single-tenant mode or multi-tenant modes. Deploy anywhere! There are no environmental dependencies.

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ElegantJ BI

MARCH 16, 2022

There are many benefits to Embedded BI approach including: World-Class Data Architecture provides access to a wealth of data sources and data warehouses, and accommodates business application architecture with single-tenant mode or multi-tenant modes. Deploy anywhere! There are no environmental dependencies.

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ElegantJ BI

MARCH 16, 2022

There are many benefits to Embedded BI approach including: World-Class Data Architecture provides access to a wealth of data sources and data warehouses, and accommodates business application architecture with single-tenant mode or multi-tenant modes. Deploy anywhere! There are no environmental dependencies.

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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.

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Data Warehouse Data Modelling Business Intelligence Business Intelligence 52

BizAcuity

JULY 13, 2021

In many cases, source data is captured in various databases and the need for data consolidation arises and typically it takes around 6-9 months to complete, and with a high budget in terms of provisioning for servers, either in cloud or on-premise, licenses for data warehouse platform, reporting system, ETL tools, etc.

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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.

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Timo Elliott

JANUARY 6, 2022

Data is delivered in context, enabling you to make better business decisions faster. Data sense-making. Storing data isn’t enough.

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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.

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