Should Your Next Data Warehouse Be In The Cloud?
Does a cloud data warehouse strategy fit into the enterprises’ analytics strategy? As companies brace with the reality of becoming more data-driven to get better insights and achieve top-of-the-line revenue, experts emphasise the only solution is to turn to a cloud data warehouse that can be provisioned quickly and provides access to faster insights. In the past, companies resisted implementing a data warehouse in the cloud due to security concerns. The key difference between an on-premise database and cloud-based database is that the latter is designed keeping elasticity in mind. In terms of functionality, cloud data warehouse requires a completely different approach to loading data, querying and moving the data around for using it for workloads. Since one has to function without interfacing with the hardware, there is a service layer that allows IT teams to manage things remotely via the cloud. As compared to an on-premise database, the cloud offers a slew of benefits. The key advantage is in terms of elasticity which allows one to plan, procure and maintain the data warehouse efficiently. Unlike on-premise data warehouse, one doesn’t have any hardware constraints, related to the number of nodes or disks one has to buy upfront. Here Are The Top Five Reasons Why Enterprises Are Turning To The Cloud: Cloud data warehouse acts as an analytics sandbox: Instead of migration an existing data warehouse to the cloud, organisations build out their new applications in the cloud. The cloud serves as a test environment to conduct PoCs and as reports suggest, data science teams use it as analytics sandbox. On the other end of the spectrum,  business development teams use it to build data marts Cloud vendor market is growing: Another reason why there’s been an upsurge in cloud data warehouses is because the IT teams need not wait for legal and procurement departments to deploy a cloud data warehouse. Leading cloud vendors AWS Marketplace, Microsoft Azure and Google Cloud take care of the installation and administration of the hardware and software and also manage the interoperability Scalability and elasticity: One of the biggest advantages offered by the cloud is that it is scalable and elastic. Hence, organizations and small businesses can do it by adding more servers online. Plus, the IT teams can dynamically add capacity to handle peak loads using built-in scripts or shift capacity to different workloads (e.g., database, ETL, BI) on a schedule. Cloud data warehouses help teams maximise the usage and offer a more efficient and budget-friendly cloud computing platform Tailored for analytics workloads: A cloud data warehouse is architected for analytics workloads on very large datasets. In cases where companies are grappling with huge, complex data sets, cloud data warehousing is the perfect solution. According to Ciarán Dynes, Vice President of Products, Talend, cloud data warehousing can be a channel for bringing structured data from legacy on-premises data warehouses together with newer big data sources Can be tested on an initial set of use cases: at a time when the digital transformation is imperative, cloud data warehousing allows organisations to tap into unstructured data seamlessly. That’s the reason companies turn to the cloud for streaming, batch and machine-learning use cases, enabling companies to uncover deep insights. One of the key use cases where the cloud is being tapped into is to gain deeper insights and understand the multiple customer touchpoints across all the channels – social, in-person, marketing analytics, data collected from automation systems. Since there are numerous user touchpoints for marketing, the data points generated are huge and can be effectively analysed within a cloud data warehouse
Does a cloud data warehouse strategy fit into the enterprises’ analytics strategy? As companies brace with the reality of becoming more data-driven to get better insights and achieve top-of-the-line revenue, experts emphasise the only solution is to turn to a cloud data warehouse that can be provisioned quickly and provides access to faster insights. In […]
The key difference between an on-premise database and cloud-based database is that the latter is designed keeping elasticity in mind.
["Cloud Computing", "cloud storage", "data warehouse"]
["data science", "Go", "AWS", "AI", "cloud computing", "Azure", "ML", "R", "Scala", "Cloud Computing", "analytics", "cloud storage", "data warehouse"]
["AI", "ML", "data science", "analytics", "cloud computing", "AWS", "Azure", "R", "Go", "Scala"]
Richa Bhatia is a seasoned journalist with six-years experience in reportage and news coverage and has had stints at Times of India and The Indian Express. She is an avid reader, mum to a feisty two-year-old and loves writing about the next-gen technology that is shaping our world.