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Read MoreWith the rise in popularity of cloud computing, data warehouses on cloud are the new standard. Time was when businesses had to buy hardware, create and maintain server rooms, and then recruit and train a dedicated team of professionals for running the whole show. Today, cloud-based data warehouses serve the same function and so much more.
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A data warehouse is a database that collects and maintains all the historical and current data that a business collects from multiple sources. This data can be accessed and analysed to help in running the business. The data itself may be structured or semi-structured in format. The data collected may be from marketing automation, point-of-sale transactions, customer relationship managements, and so on. Traditional or on-premise data warehouses tend to have high operational overhead costs, rigid or fixed storage capacities, and prone to technical issues. Due to these inherent issues with traditional data warehouses, more and more businesses are turning to cloud data warehouses.
Here is a closer look at some of the benefits of cloud data warehousing that was touched upon earlier:
A core characteristic of cloud data warehouses is that they are elastic; they can be effortlessly scaled up or down as per the requirements of the business. This elasticity is a core characteristic of cloud computing itself. The scaling is done seamlessly without any impact on the performance of the data warehouse or the data availability.
Cloud data warehouses have had a huge impact on data analytics and data science. Machine learning/artificial intelligence (AI) and Cloud data warehousing has helped businesses to make better decisions and predict business outcomes by accessing, reporting, and analysing huge amounts of data with ease.
Traditionally, the collection, processing, and analysis of real-time data were a challenging activity. Both the velocity and the volume of real-time data may differ widely. Cloud data warehousing has proven to be an answer to the challenges posed. It supports real-time streaming data and handles the differing data streams easily, thus, allowing businesses to make quick and informed business decisions based on real-time insights.
Traditional data warehouses have limitations on their resources and scaling capacities, which could potentially affect performance. By contrast, cloud infrastructure ensures that scaling is done seamlessly and that there is considerably quicker uptime. Moreover, cloud providers are obligated to meet service-level agreements (SLAs) that promise quick uptimes. Leading cloud providers offer 99.9% uptimes. There is also automatic data backup with cloud data warehouses.
Businesses no longer have to recruit and train a team of professionals to manage and maintain on-site data warehouses. All the hassles of managing a cloud data warehouse are outsourced to the cloud providers. This frees the IT departments of businesses to focus on business activities. Security is managed by the cloud provider who has to ensure data and infrastructure safety.
Businesses that go for cloud data warehousing save a lot on costs. Businesses would typically spend valuable capital on hardware, and all other expenditures associated with traditional data warehouse solutions which are run 24/7 regardless of how many resources are actually in use. In contrast, with cloud warehousing businesses can pay for what they use or choose a predictable flat-rate payment option. Cloud providers vary in how they charge. Nevertheless, the costs associated with cloud data warehouses are typically much lesser compared to on-premise data warehouses.
There are two broad categories of cloud data warehouse architecture: clustered or serverless. With clustered data warehouses the customer contracts or expands the cluster size as data and load contract or expand. Here the cluster capacity and health management are sometimes required. The cost is easier to predict as it is priced per node. Cluster-based cloud data warehouses are the older deployment architecture. Azure SQL Data Warehouse and Amazon Redshift are examples of this type.
Serverless data warehouses are the more modern cloud data warehouse architecture. There are no clusters to manage and queries are scaled automatically up to a set throttle point. Management is taken care of by the cloud service provider. The cost may be unpredictable as it is utilisation or per query based. Google BigQuery and Snowflake are examples of serverless data warehouses.
Some of the top cloud data warehouse solutions and providers are as follows:
Cloud data warehousing has been a game changer for businesses. In the process of successfully leveraging big data, cloud data warehousing has made a profound impact in the field of data science and analytics. Cloud data warehousing is now proving to be the key to successful business operations and impactful business decisions.
The Asia Sourcing Portal (ASP) is an intranet-based web portal designed to streamline the supplier onboarding procedure and facilitate the direct updating of SKU prices into the organization's legacy backend system through automation.
