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?

Data Warehouse 52

Data Warehouse Agile Data Modelling Data Quality 52

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 .

Data Warehouse 52

Data Warehouse IBM Maintenance IBM Support Data Architecture 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

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

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?

Data Warehouse 52

Data Warehouse Cloud Computing Data Management Data Governance 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

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. The combination of data vault and information marts solves this problem.

Agile 52

Agile Data Warehouse Data Quality Government 52

Smart Data Collective

MAY 16, 2022

Data management software helps in reducing the cost of maintaining the data by helping in the management and maintenance of the data stored in the database. It also helps in providing visibility to data and thus enables the users to make informed decisions. They are a part of the data management system.

Data Management 327

Data Management Data Mining Data Warehouse Data Modelling 327

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.

Data Warehouse 52

Data Warehouse Cloud Computing Cybersecurity Data Modelling 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

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

Smart Data Collective

JULY 9, 2023

By understanding the power of ETL, organisations can harness the potential of their data and gain valuable insights that drive informed choices. ETL is a three-step process that involves extracting data from various sources, transforming it into a consistent format, and loading it into a target database or data warehouse.

Data Warehouse 223

Data Warehouse Data Quality Data Analytics Data Analytics 223

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

Actian

JUNE 4, 2019

Implementing a data warehouse is a big investment for most companies and the decisions you make now will impact both your IT costs and the business value you are able to create for many years. Data Warehouse Cost. Your data warehouse is the centralized repository for your company’s data assets.

Data Warehouse 40

Data Warehouse Digital Transformation Data Quality Data Modelling 40

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 Data Quality Cloud Computing Monitoring 52

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 Data Quality Cloud Computing Monitoring 52

BizAcuity

APRIL 1, 2023

Introduction Teradata is an integrated platform that provides functionality to store, access, and analyze organizational data on the Cloud as well as On-Premise infrastructure. Teradata is based on a parallel Data Warehouse with shared-nothing architecture. Data is stored in a row-based format.

Data Warehouse 130

Data Warehouse Monitoring Planning Data Modelling 130

BizAcuity

SEPTEMBER 22, 2022

Teradata is an integrated platform that provides functionality to store, access, and analyze organizational data on the Cloud as well as On-Premise infrastructure. Teradata is based on a parallel Data Warehouse with shared-nothing architecture. Data is stored in a row-based format. Not being an agile cloud data warehouse.

Data Warehouse 130

Data Warehouse Monitoring Planning Data Modelling 130

Timo Elliott

JANUARY 6, 2022

The point of finding your dark data is to generate insight from it. To this end, SAP offers a wide range of tools that support the following capabilities: Data orchestration. Information landscapes are complex. Data is delivered in context, enabling you to make better business decisions faster. Data sense-making.

Chief Data Officer 338

Chief Data Officer Embedded Analytics Data Governance Data Warehouse 338

Smart Data Collective

JUNE 16, 2022

Data is fed into an Analytical server (or OLAP cube), which calculates information ahead of time for later analysis. A data warehouse extracts data from a variety of sources and formats, including text files, excel sheets, multimedia files, and so on. Types: HOLAP stands for Hybrid Online Analytical Processing.

Data Warehouse 331

Data Warehouse Data Modelling Monitoring Business Intelligence 331

Astera

JULY 3, 2024

This seamless integration allows businesses to quickly adapt to new data sources and technologies, enhancing flexibility and innovation. Supports decision-making A robust data framework ensures that accurate and timely information is available for decision-making.

Data Architecture 40

Data Architecture Data Warehouse Data Governance Government 40

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

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

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.

Data Warehouse 130

Data Warehouse Artificial Intelligence Data Analytics Data Analytics 130

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

Timo Elliott

DECEMBER 14, 2022

Gartner calls it the Composable Enterprise , for example – it’s about having a solid information foundation that enables fast and flexible creation of what they call composable applications that allow you to create new applications and workflows by just bringing together modular components. Business Context. Business Content.

Innovation 264

Innovation Artificial Intelligence Data Warehouse Government 264

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

Analysts Corner

JUNE 18, 2023

ETL Developer: Defining the Role An ETL developer is a professional responsible for designing, implementing, and managing ETL processes that extract, transform, and load data from various sources into a target data store, such as a data warehouse. Oracle, SQL Server, MySQL) Experience with ETL tools and technologies (e.g.,

Data Warehouse 130

Data Warehouse Data Quality Documentation Data Governance 130

Smart Data Collective

NOVEMBER 18, 2020

Definition: Data Mining vs Data Science. Data mining is an automated data search based on the analysis of huge amounts of information. Complex mathematical algorithms are used to segment data and estimate the likelihood of subsequent events. Data Mining Techniques and Data Visualization.

Data Mining 358

Data Mining Big Data Artificial Intelligence Data Warehouse 358

Timo Elliott

NOVEMBER 30, 2022

In every case, it involves having a solid information foundation that enables fast and flexible creation of what Gartner calls Composable Applications that allow you to create new applications and workflows by bringing together modular components. The problem is that we’ve been doing analytics wrong for thirty years.

Innovation 246

Innovation Vision Data Warehouse Logistics 246

Astera

NOVEMBER 30, 2023

With rising data volumes, dynamic modeling requirements, and the need for improved operational efficiency, enterprises must equip themselves with smart solutions for efficient data management and analysis. This is where Data Vault 2.0 It supersedes Data Vault 1.0, What is Data Vault 2.0? Data Vault 2.0

Data Warehouse 52

Data Warehouse Big Data Healthcare Data Governance 52

Insight Software

JANUARY 20, 2021

In order to achieve that, though, business managers must bring order to the chaotic landscape of multiple data sources and data models. That process, broadly speaking, is called data management. Pile on external data from suppliers and external service providers, and it begins to appear unmanageable.

Data Management 95

Data Management Data Analytics Data Analytics E-Commerce 95

Sisense

JULY 8, 2020

Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive. In recent years we’ve seen data become vastly more available to businesses. This has allowed companies to become more and more data driven in all areas of their business.

Data Warehouse 90

Data Warehouse Embedded Analytics Real-time Data Documentation 90

Astera

AUGUST 21, 2023

Introduced in 1996 by Ralph Kimball, a star schema is a multi-dimensional data modeling technique. It is the simplest schema type businesses use in data warehousing. This simple, denormalized structure makes it very efficient for querying data. Increased costs: Adding redundant data increases computing and storage costs.

Data Warehouse 52

Data Warehouse Data Modelling Data Quality Visualization 52

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. On the face of it, the idea is simple: Fact tables contain transactional information, and dimensions provide context to these facts through foreign key relationships.

Data Warehouse 52

Data Warehouse Data Modelling Business Intelligence Business Intelligence 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

Sisense

JUNE 26, 2019

You need to find the right data sets, clean them up, and test out interoperability. But you also need to deliver comprehensible insights, make changes on the fly, and continue to deliver the most up-to-date information from the latest data available. Enterprise companies usually have legacy systems that contain important data.

Data Warehouse 75

Data Warehouse Data Modelling Big Data Monitoring 75