Smart Data Collective

JULY 9, 2023

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. Extract The extraction phase involves retrieving data from diverse sources such as databases, spreadsheets, APIs, or other systems.

Data Warehouse 264

Data Warehouse Data Quality Data Analytics Data Analytics 264

Smart Data Collective

NOVEMBER 18, 2020

Data Mining Techniques and Data Visualization. Data Mining is an important research process. Practical experience. It is not very interesting to be engaged exclusively in theory, it is important to try your hand at practice.

Data Mining 360

Data Mining Big Data Artificial Intelligence Data Warehouse 360

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

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

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

Timo Elliott

DECEMBER 14, 2022

Most innovation platforms make you rip the data out of your existing applications and move it to some another environment—a data warehouse, or data lake, or data lake house or data cloud—before you can do any innovation. Business Context. Business Content.

Innovation 264

Innovation Artificial Intelligence Data Warehouse Government 264

Astera

NOVEMBER 1, 2023

It serves as the foundation of modern finance operations and enables data-driven analysis and efficient processes to enhance customer service and investment strategies. This data about customers, financial products, transactions, and market trends often comes in different formats and is stored in separate systems.

Data Warehouse 52

Data Warehouse Finance Data Quality Banking 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.

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 28, 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

Astera

DECEMBER 29, 2023

Among the key players in this domain is Microsoft, with its extensive line of products and services, including SQL Server data warehouse. In this article, we’re going to talk about Microsoft’s SQL Server-based data warehouse in detail, but first, let’s quickly get the basics out of the way.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 52

Astera

DECEMBER 29, 2023

Among the key players in this domain is Microsoft, with its extensive line of products and services, including SQL Server data warehouse. In this article, we’re going to talk about Microsoft’s SQL Server-based data warehouse in detail, but first, let’s quickly get the basics out of the way.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 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.

Data Modelling 52

Data Modelling Data Warehouse Banking Real-time Data 52

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

Timo Elliott

NOVEMBER 30, 2022

Because of technology limitations, we have always had to start by ripping information from the business systems and moving it to a different platform—a data warehouse, data lake, data lakehouse, data cloud. The problem is that we’ve been doing analytics wrong for thirty years.

Innovation 246

Innovation Vision Data Warehouse Logistics 246

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.

Data Warehouse 52

Data Warehouse Data Quality Big Data Predictive Analytics 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

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.

Data Warehouse 52

Data Warehouse Data Modelling Agile Data Management 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 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

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

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.

Data Warehouse 130

Data Warehouse Monitoring Planning Data Modelling 130

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.

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

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.

Data Warehouse 130

Data Warehouse Monitoring Planning Data Modelling 130

Actian

JULY 30, 2019

Data warehouse modernization. Move your Netezza, Teradata or Exadata data warehouse that likely runs on obsolete, proprietary hardware to a shiny new system that runs in the cloud, costs a fraction of what you were paying before and can be turned on and off like a light switch. Sounds like a no-brainer. Is it that easy?

Data Warehouse 8

Data Warehouse Data Modelling Data Analytics Data Analytics 8

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

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

The BAWorld

FEBRUARY 18, 2025

Works with datasets to discover trends and insights, maintaining data accuracy. Power BI Data Engineer: Manages data pipelines, integrates data sources, and makes data available for analysis. Creates data models, streamlines ETL processes, and enhances Power BI performance.

Data Modelling 40

Data Modelling Data Warehouse Data Security Government 40

Sisense

JULY 7, 2020

In-Warehouse Data Prep provides builders with the advanced functionality they need to rapidly transform and optimize raw data creating materialized views on cloud data warehouses. In-Warehouse Data Prep supports both AWS Redshift and Snowflake data warehouses. Additional capabilities.

Data Warehouse 92

Data Warehouse Agile Data Modelling Innovation 92

Sisense

DECEMBER 3, 2019

The rapid growth of data volumes has effectively outstripped our ability to process and analyze it. The first wave of digital transformations saw a dramatic decrease in data storage costs. On-demand compute resources and MPP cloud data warehouses emerged. Optimize raw data using materialized views.

Embedded Analytics 90

Embedded Analytics Data Warehouse Digital Transformation Digital 90

Sisense

JULY 22, 2020

They hold structured data from relational databases (rows and columns), semi-structured data ( CSV , logs, XML , JSON ), unstructured data (emails, documents, PDFs), and binary data (images, audio , video). Sisense provides instant access to your cloud data warehouses. Connect tables.

Digital Transformation 98

Digital Transformation Data Warehouse IBM Support IBM cost 98

Sisense

JUNE 26, 2019

We have often talked about the single-stack approach to business analytics, and with the complexity of enterprise data, this approach makes even more sense. . You want to make sure you have one place to bring in all your data and do your data modeling. In this case, you may want to connect live to these sources.

Data Warehouse 75

Data Warehouse Data Modelling Big Data Monitoring 75

Insight Software

JANUARY 20, 2021

Organizations that can effectively leverage data as a strategic asset will inevitably build a competitive advantage and outperform their peers over the long term. In order to achieve that, though, business managers must bring order to the chaotic landscape of multiple data sources and data models.

Data Management 95

Data Management Data Analytics Data Analytics E-Commerce 95

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