Companies have multiple options with which to address the flood of data that they need to leverage to make intelligent business decisions. Databases are the logical places to store their information resources and have become increasingly important as organizations struggle to take advantage of the possibilities of using big data for advanced analytics. Data warehouses offer a technology that can increase the utility of an organization’s intellectual capital and augment the power of their data.
What is a Data Warehouse?
A data warehouse acts as a repository for the data that is gathered and generated from an enterprise’s operational systems. A data warehouse differs from a database in its ability to process data from different sources. Some of those sources may be other databases. A database falls into the category of an online transaction processing (OLTP) application with the data they process primarily coming from primary sources. A data warehouse supports online analytical processing (OLAP) and organizes information from a variety of sources to facilitate using it for in-depth analysis.
There are three main components of a data warehouse. They are:
Data warehouses offer organizations both business and IT-related benefits such as:
The Snowflake Cloud Data Warehouse
Snowflake is a software as a service (SaaS) data warehouse solution that has been in existence since 2012. The company has experienced tremendous growth since its founding and shows no signs of slowing down. Its success is fueled by its capacity to help businesses make their data more accessible for use for analytics in the cloud. An organization’s data is uploaded to Snowflake where it is made available to BI tools. Customers can choose a pay-for-use or subscription model when working with Snowflake.
Some of the specific characteristics of Snowflake that make it attractive to customers are associated with it being an SaaS offering. It is not a software application that can be installed on a user’s systems and it cannot be run on private cloud infrastructures. The Snowflake support team handles all maintenance, management, and tuning of the system. There are no hardware or software considerations that impact a Snowflake client. It is a self-contained data warehouse environment hosted entirely on public cloud infrastructure.
Aqua Data Studio Integrates With Snowflake Data Warehouses
Aqua Data Studio for Snowflake offers users a comprehensive toolkit with which to interact with the information stored in your Snowflake data warehouse as well as your other data sources. Aqua Data Studio is a valuable tool that enables your database team to access all their environments from a unified platform. Its features will improve the productivity of your team and enable valuable interpretation and presentation of your data resources.
The first step is to register your Snowflake data warehouse. After this is done, you can access it in your list of data sources. Some of the features that make Aqua Data Studio a productive tool are its intuitive and graphical query builder and analyzer which helps users negotiate the syntactical differences required when working with Snowflake. ER Modeler furnishes the ability to perform forward and backward engineering to explore ER diagrams and extract ER models from existing databases. Aqua Data Studio also provides a rich scripting environment and the capability to use Snowflake as the foundation for visual analytic presentations.
The combination of Aqua Data Studio and a Snowflake data warehouse provide any organization with tools that can turn its data assets into actionable business intelligence. A video providing an overview of how Aqua Data Studio integrates with Snowflake is available and illustrates the multiple features of this flexible application. Give it a look and see how you can make more from your Snowflake instances with Aqua Data Studio.
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