How Serverless Data Warehouse can add Value to a Business?

Data warehousing is a process for gathering and managing data from various sources to provide meaningful business insights. A data warehouse is generally used to connect and analyse business data from heterogeneous sources. The data warehouse is the core of the business intelligence (BI) system that is built for data analysis and reporting.

It is a blend of technologies and components that aids the strategic use of data. It is the electronic storage of a massive amount of information by a business which is designed for question and analysis instead of transaction processing. Data warehousing is a process of transforming and making it available to users promptly to make a difference.

A manufacturer needs to modernise its data management system and leverage the data collected over the years with a sophisticated data storage system to expand the business across the globe. For that, the manufacturer needs to be transformed into a data-driven organisation by migrating the data from on-premise databases to a serverless data warehouse.

A serverless data warehouse will get its functional building blocks via serverless third-party service, or a set of services. These services are fully managed by the serverless data warehouse. It handles significant complexities like security, reliability, efficiency, and costs optimisations, and delivers a consumption-based billing model for their usage.

MarketsandMarkets report reveals that the global serverless architecture market will reach US$21.1 billion by 2025 from US$7.6 billion in 2020 at a CAGR of 22.7%. The three key factors to improve data management are:

• Flexibility to shift from CAPEX to OPEX

• Minimise the infrastructure cost

• Exclude the requirement to manage servers

Data Accessibility and Seamless Management

Data generated from various sources now can be made available to businesses to improve their decision making and devising business strategies across functions. The traditional systems cannot handle multiple formats they are available in. Manual intervention is needed to integrate them all into one format, which can be time-consuming and prone to errors.

A cloud-based serverless data warehouse can automate data management process. It can make data readily available and accessible for advanced analytics and to get insights into enhancing business processes and efficiencies.

Benefits of Serverless Data Warehouse

• Benefits of opting for a serverless data warehouse as followed:

• Accessibility from any region across the globe that improve decision-making process

• Reliable cloud providers help focusing on core business

• Its solution makes the management cost effective

• Offers columnar storage and parallel processing

• Automates data distribution and ensures data security

Hurdles in Migration

Although a serverless data warehouse offers you seamless data management, it comes with some challenges as well. You need to select the right building blocks because all of them are not fully managed. For example, Amazon Redshift requires you to pick up the node type that is storage optimized. You will require choosing the number of compute nodes for the integration and manually sizing them.

In some cases, you might need to cluster different serverless building blocks and come up with a solution using non-serverless blocks. You may consider incorporating individual blocks instead of having one single solution for your business. Improving configuration might make the solution complex.

Collaborating with the Experienced Data Experts

Figuring these hidden complexities requires an in-depth understanding of data, data warehouses and the service providers. An experienced solution provider can work closely with you to understand your needs and deliver as per your requirements.

For instance, Indium provides a simple, secure, cost-effective and scalable solution. Having expertise in data modelling, it derives the technology architecture by analysing the process architecture, business rules, tools, metadata management, and security considerations.

The data integration and processing tools, middleware, database management and related technologies are also other factors to be considered.

For the serverless data warehouse architecture, data pipeline and transformation is done step by step. Consequently, the entire cycle of storage, retrieval, processing data within the data warehouse is planned. The architecture is designed to make sure that the workload is processed on time, optimising performance and reducing cost.