Understanding Data Warehouse As A Service And Its Benefits

Today's data-driven business world is quite competitive, and to grow and survive, organizations must have access to the right data integration platform. In every organization, massive amounts of data are generated daily, and the organization that does not use such information fails to sustain itself in the market.

Manual processes are basically prone to more errors, and there also might be a loss of data while carrying them out. Additionally, they take a lot of time and with an increase in complexity, it is becoming very challenging to depend on manual methods. Moreover, manual processes are also a setback to business growth. Every little change that organizations want to see for their data will take a lot of time to reflect, and the entire data analytics process in itself becomes very tedious.

Owing to these challenges, businesses find investing in data warehousing far better than the manual processes and maintaining a regular database. After all, if organizations have to stay competitive in today's world, they must have to work towards a smart and intelligent strategy by leveraging technological advancements to keep pace with the market competition. So, a data warehouse is one of the most crucial elements that every business must have in the present era. Let's dive in to know more about data warehouses.

A data warehouse is a data management system designed to support and enable business intelligence activities, mainly analytics. Data warehouses are solely intended to perform analysis and queries and often contain huge amounts of historical data. The data within a DW is usually derived from a wide array of sources like transaction applications and application log files.

A data warehouse consolidates and centralizes massive amounts of data from disparate sources. Its analytical capabilities give organizations to derive valuable business insights from their data to improve and enhance decision-making. Data warehousing gives Business Intelligence users to have structured data to form insights. Moreover, it builds a historical record that can be invaluable to business analysts and data scientists. Because of these abilities, a data warehouse can be considered an organization's "single source of truth."

In the present business environment, staying competitive and meeting customer expectations requires tackling the power of business data. But, with the humongous growth of data sources and information volumes driven by tech advancements, storing and managing this info has become increasingly important.

It’s requisite to be aware of the challenges that come up during the setup of your data warehousing solution. Listing here some of the immediate complexities of DWaaS:

1. Data Integration: Organizations often have different data formats and sources, making data integration challenging. DWaaS needs effective data integration processes to make sure that data from numerous sources can be seamlessly loaded into the DW. Companies must plan and implement apt data integration strategies to ensure the data warehouse can tackle disparate data types and formats.

2. Performance and Scalability: As data volumes climb, the scalability and performance of the DWaaS become significant. While DWaaS provides scalability options, companies must optimize and monitor their data models, queries, and indexing strategies to ensure structured performance. Evaluating the DWaaS abilities and performance guarantees before adopting their services is essential.

3. Data Governance and Compliance: Maintaining compliance and data governance can be complex in a DWaaS environment. Companies must mandate that data governance policies, compliance standards, and regulatory requirements are followed effectively. This involves - data lineage, managing data access permissions, audit trails, and adherence to industry-specific regulations.

4. Data Security: Data security is a crucial concern when utilizing DWaaS. Since the data resides on a cloud platform managed by a 3rd-party provider, there is always a risk of data breaches or unauthorized access. Ensuring the DWaaS has solid security measures, involving access controls, encryption, and regular security audits, is paramount.

5. Data Latency: There may be data latency problems depending on the geography of the DWaaS servers and the distance from the companies' data sources. Slow data transfer and query response times can whack decision-making and real-time analytics. It is crucial to evaluate the network infrastructure and consider the proximity of data sources to minimize latency.

DWaaS is an attempt to allow businesses to focus on what they do best and not let issues around storage and resources to get in the way.

The 'As-a-Service' model focuses on providing various services to clients through the Internet. Dropbox is a famous example of such a service. Along with these services, clients are provided with the benefits of low cost and scalability. This model includes SaaS, PaaS, and IaaS and has become a means to enable technologies through digitalization, analytics, and automation. DWaaS is the latest addition of data warehouse to the 'as-a-service model.

A data warehouse is a repository that stores data integrated from heterogeneous sources. This data is then used either for analysis or is accessed by the user for decision-making. DWaaS uses the concept of 'As-a-Service' to provide its audience with the experience of data warehousing over the cloud. The demand for access to real-time data that's high on volume, velocity, and veracity is one of the primary reasons for the emergence of DWaaS.

You may also read - Data Lake as a service

#1. Data Accessibility To Business Users

The visibility into data is the chief concern of business users as it lets them make informed decisions. This is achieved by resource pooling to share storage space, networks, and computing power in cloud data warehouses. It results in providing data marts for new users without limiting the storage or processing power. Also, ad-hoc queries can be performed on the same dataset by stakeholders from different locations.

#2. Enhanced Performance And Speed

The ever-increasing data from numerous resources demands an effective data management solution. This has given rise to DWaaS that offers cloud data warehouse service to improve the overall performance, efficiency, and speed of data analysis and processing within an organization. Typically, DWs present on the cloud emphasises various servers that accelerate the processing speed. Furthermore, it can seamlessly integrate with new data sources.

#3. High Data Storage Capacity

Earlier, IT teams were purchasing huge storages that cost them a fortune. Simultaneously, the cloud data warehouse allows them to decide the storage limit according to their present needs. However, organizations can easily scale up anytime with an additional cost which is quite economical. What's more? It offers agility and flexibility that allows firms to quickly deploy a change without affecting the organization's architecture or budget.

#4. Quick Disaster Recovery

The conventional recovery methods are way too expensive and defenseless, whereas the cloud data warehouse gives sheer backup security. The good thing is it doesn't even need any additional hardware as it supports data duplication naturally. It instantly snapshots the processes and saves them automatically. With a data warehouse in place, it holds the data in different nodes to make the duplicate data seamlessly accessible. DWaaS service providers provide specialized networks to improve backup security further.

#5. Shared Cost Of Ownership

Unlike the mighty cost involved in the on-premise DWs, cloud data warehouses are economical, which is the main reason for their popularity. It does not require maintenance, expensive hardware, or continuous updates as everything is taken care of by the service provider. The management can purchase just the necessary amount of storage and compute power, which can be extended as required. Besides, DWaaS does not demand networking or server rooms.

Here are some instances of how data warehousing is used across the board. Let's look at various industries that consider data warehouses an essential part of their day-to-day operations.

Investment and Insurance sector

Data warehouses in the investment and insurance sector are primarily used to analyze customer and market trends and other data patterns. Forex and stock markets are two significant sub-sectors where DW plays a significant role as a single point difference can lead to immense losses across the board. In this sector, data warehouses are typically shared and focus on real-time data streaming.

Retail chains

A data warehouse in the retail sector is majorly used for marketing and distribution to examine pricing policies, enable tracking of items, analyzing customer buying trends, and keep track of promotional deals. Retail chains usually implement enterprise data warehouses for forecasting and business intelligence needs.

Healthcare

Data warehouses in the healthcare sector are utilized to - generate treatment reports, forecast outcomes, research labs, share data with insurance providers, and other medical units. EDW is the backbone of healthcare systems because the latest, up-to-date treatment information is crucial for saving lives.

Therefore, a data warehouse is significant for any business that wants to scale its business operations and become a well-known name in the data-driven business landscape. At Polestar solutions, we have a team of data warehouse professionals who have worked on complex and sophisticated enterprise-level data warehouses.

Our consultants have architected processes & systems that have not only optimized for the present needs but are also scalable to meet future demands. So, if you are looking to implement a data warehouse into your business operating systems, reach out to us.