What are data warehouse solutions? (With 10 examples)
By Indeed Editorial Team
Published 15 June 2022
The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.
Business operations can entail processing large amounts of data from different departments. Data warehouses are a popular business intelligence tool that can help companies make important decisions regarding their future direction. Learning about data warehouses can help you store and manage business data more effectively. In this article, we explain what a data warehouse solution is and provide a list of 10 cloud data warehouse solutions for you to consider.
What are data warehouse solutions?
Data warehouse solutions refer to databases that collect information from various departments within a company. A data warehouse supports data analysis by gathering and categorising figures and statistics from various departments such as sales, marketing and research. While a standard database collects data, a data warehouse can also analyse and sort it into different categories. This creates a centralised data system within an organisation that can help facilitate more effective communication and the implementation of impactful policy across all departments.
A data warehouse also converts the information into readable dashboards that the whole company or separate departments can view and use. It's one of the main tools that businesses use for business intelligence, meaning an organisation's effort to analyse past data to create strategies for the future.
Cloud vs on-premises data warehouses
There are two main types of data warehouses, including on-premises and cloud. An on-premises data warehouse describes when the physical server that stores data and runs analytics is on the premises of the business itself, whereas a cloud data warehouse is a system that operates in the cloud. This kind of warehouse solution entails transferring your data to a central server system that a cloud service provider hosts. Here are the benefits of each type:
An on-premises data warehouse allows companies to have total control over data without the data leaving the company's system. The advantages of on-premises data warehouses are that they typically have fast processing and vast storage facilities. A key benefit of an on-premises data warehouse is that in the event of any issues with internet connectivity, it's likely you can still access your data.
The benefits of cloud-based data warehouses include cost-efficiency and scalability. Cloud service providers can increase the storage of a company's data warehouse with ease. This means that a cloud-based system may be more desirable for a business that's growing rapidly and for those that don't have the capability to construct their own data warehouses.
What do organisations use data warehouses for?
Organisations may use a data warehouse as a tool to inform their business decisions. By creating reports on historical data regarding a company's operations, a data warehouse can identify the systems and processes in an organisation that are running efficiently and those that require improvement. By ranking the performance of different products or services, a data warehouse creates a visual representation that highlights what practices are performing the best for the business. Using a data warehouse may also increase the effectiveness of business intelligence to secure a company's long-term growth.
10 cloud data warehouse solutions to consider
Here are 10 warehouse solutions for you to consider:
1. Azure Synapse
Azure Synapse from Microsoft is an analytics platform that incorporates data integration, enterprise data warehousing and big data analytics. It allows users to query data with the use of a serverless or dedicated resource. It provides an integrated experience for exploring, preparing, managing and serving data for business intelligence and machine learning. It also has advanced security and privacy features.
2. Google BigQuery
Google BigQuery from Google Cloud is a fully-managed enterprise data warehouse for analytics built upon the Google Cloud Platform. It functions without a server and allows companies to analyse any data set, and it has a streaming ingestion feature that gathers data in real-time. It also allows users to share insights through datasets, queries, spreadsheets and reports.
3. IBM Db2 Warehouse
IBM Db2 Warehouse from IBM is a client-managed, preconfigured data warehouse. It runs in private and virtual private clouds along with other supported infrastructures. It has built-in machine learning, automated scaling and built-in analytics. It also features flexible deployment, which means a user can create an application once and move it to another location with no or minimal modifications.
4. Amazon Redshift
Amazon Redshift from Amazon Web Services is a fully managed cloud data warehouse that allows customers to scale their requirements. It allows a user to upload any data set and conduct data analysis queries. Redshift has fast query performance irrespective of the size of the data set, using popular SQL-based tools and various business intelligence applications.
5. SAP Data Warehouse Cloud
SAP Data Warehouse Cloud from SAP is a data warehouse service built on the SAP HANA Cloud database. It can connect data across multi-cloud and on-prem repositories in real-time whilst maintaining the business context. It features prebuilt data models and enables users to model, visualise and share data within a managed environment
6. Oracle Autonomous Data Warehouse
Oracle Autonomous Data Warehouse from Oracle is a cloud data warehouse service that allows organisations to secure their data. It also allows companies to create data-driven applications and automates various processes including configuring, tuning, scaling and also backing up the data warehouse. It has built-in coverage for database capabilities that allow data queries across multiple data types and machine learning analysis. In addition, it features tools that enable self-service data loading, data transformations, business modelling and automatic insights.
7. Teradata Vantage
Teradata Vantage from Teradata offers a broad spectrum of data management solutions, including database management, cloud data warehousing and data warehouse appliances. Its product portfolio is available through its own managed cloud and also on Amazon Web Services or Microsoft Azure. It enables organisations to run a range of diverse queries, in-database analytics and complex workload management.
The data warehouse from Panoply automates data management tasks related to running big data in the cloud. The Panoply Smart Data Warehouse requires no schema, modelling or configuration. It also has an ETL-less integration pipeline that connects to structured and semi-structured data sources.
9. Snowflake Cloud Data Platform
The Snowflake Cloud Data Platform offers a cloud data warehouse built upon Amazon Web Services. It can load and optimise data from almost any source, both structured and unstructured. It supports standard SQL, and the tool requires no management and no infrastructure.
10. Yellowbrick Data Warehouse
Yellowbrick Data provides a data warehouse for distributed clouds that's easy to use and allows users to organise in private data centres, public clouds and the network edge. It has a modern analytics database devised for demanding batch, real-time, interactive and mixed workloads. The company regularly implements the latest advances in software and hardware protocols, combining them with smart thinking on database architecture.
Advantages of using a data warehouse
There are several benefits for organisations if they use a data warehouse, these include:
Saves time: Data warehouses allow businesses to access essential data quickly without having to rely relying on a technical expert. This means it's easier for a business to make fast decisions based on data at any time, improving efficiency.
Improves data quality: A data warehouse can improve the quality of an organisation's data because it refines and processes the data correctly before end-users access it. This includes eliminating inaccurate or duplicate data, which helps the organisation to operate more efficiently.
Is more convenient: Data warehouses can perform queries and analyses on a particular subject or business area. This allows companies to access the data that's most relevant to a particular query or challenge in an efficient and convenient way.
Enhances business intelligence: Data warehouses can enhance the quality of business intelligence by consolidating data from multiple different sources. Cross-referencing data from different sources manually can be a complicated, challenging and time-consuming task, so by eliminating this issue, a data warehouse improves the quality and accessibility of business intelligence.
Creates consistency: Data warehouses synchronise data from multiple sources, making business intelligence data more consistent. This can improve its quality, and users can be more certain that the data is full and accurate, to support more effective decision-making.
Increases return on investment: Though data warehouses require an initial investment, they offer businesses an increased return on investment, as the organisation can use its data more effectively. This can improve business strategies and help to generate increased sales and revenues.
Stores historical data: A data warehouse allows companies to store extensive historical data more easily. Past data can be useful for analysis and effective decision making, as it can help a business understand past successes and identify how to use these strategies again.
Please note that none of the companies, institutions or organisations mentioned in this article are affiliated with Indeed.
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