Next-Generation Data Warehouses

Gautam Gupta, Vice President Enterprise Solutions, Yash Technologies | Monday, 14 October 2019, 06:23 IST

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Gautam Gupta, Vice President Enterprise Solutions, Yash TechnologiesPicture a situation like this: you are collecting and analyzing insights about product sales performance. The results make you wonder why a certain area in your organization is doing better than others. You slice, deepdive, judge, and use different perspectives to analyze and to conclusions, but can’t find the answers.

You need data to arrive at decisions but that is not available in your corporate systems. How do you access this information and quickly analyze it all to be able to make intelligent business choices?


Bring Analytics to Data

Organizations face the tough business reality of today – of bringing together people, processes, and data for a balanced approach, especially when it comes to data and analytics. The real work begins when organizations can take advantage of existing on-premise data and invest in analytics technology that creates a path to the future as more data and things shift to, and are born in, the cloud.

“With the evolution of data warehouses in the cloud, it is time to take away the complexity traditionally associated with business intelligence infrastructure and democratize data”

If users don’t want to go the traditional route of specifying and uploading and testing data, they’d need a whole new way to integrate data from on-premises and cloud sources, in other words, they require the next-generation modern data warehousing.

A typical analytics wish-list can include:

• Ability to remodel the data warehouse on demand

• Access to the data source while on the move

• Avoid duplication of data

• Evade loss of time with data-load jobs

• Facilitate analytical processing in real-time

• Decrease of data objects to be stored and maintained

Introduction to Next-Generation Data Warehouse

Today, traditional Enterprise Data Warehouse (EDW) is almost out-dated and ineffective due to the sheer volume and speed of voluminous data coming from the Cloud, social networks, mobile devices and IoT in multiple formats. The EDW is also unable to meet the expectation of accessible, meaningful and ready to be consumed data in real-time or near real-time.

Next-generation data warehouse software acts as the central storage hub for a company’s integrated data that is used for analysis and future business decisions. This information within a data warehouse comes from different departments of a company, such as sales, finance, and marketing, and others. Each of these departments may have their own data mart that is a repository for singular, precise, and relevant information. Built in two ways, a data warehouse can be either a top-down design or follow a bottom-up approach. While the former collects all data from the company at a granular level and then allocates the data to specific data marts the later creates a data mart first and then combines it to form a comprehensive data warehouse.

Data warehouses can combine data from sales force automation tools, marketing automation platforms, ERP and supply chain management suites, etc., to enable the most precise analytical reporting and intelligent decision-making. Businesses may also use predictive analytics and artificial intelligence tools to pull trends and patterns found in the data.

Here’s how the future of Next-Generation Data Warehouse looks like:

• Enterprises are turning to cloud to power and store their data warehouses. It will be adaptable, and offer real-time and past insights.

• Data warehousing is being blended into current analytics systems through the application of data virtualization.

• In all its intents and purposes, data warehouses are data analytics platforms. Companies realize that data analytical power is crucial to every aspect of their product and operations, and data warehouse technology is already delivering this power.

• Data warehousing empowers users like never before. The key advantage of data warehouse environments is the emphasis on self-service.

• Data warehousing is going to feed into data lakes, Hadoop, and Spark-as well as the other way around.

• As against the traditional EDW, next-generation warehousing is going to require fewer people to populate and operate

• Data warehousing is going to support AI and machine learning to deliver results and is going to occupy a central place in delivering an impeccable customer experience.

Next-Gen Data Warehouses to Power Intelligent Enterprises

Given the benefits in security, cost, scalability, performance and accessibility anytime and anywhere, Cloud is the cornerstone for next-generation data warehouses. With the benefit of hybrid and cloudnative platforms, next-generation data warehouses are becoming smarter in all three dimensions - services, storage, and computing infrastructure. Additionally, built-in adaptability, enterprise grade security, and protected data-sharing competences are making warehouses intelligent enough to empower users for generating insights into a selfservice consumption model.

To quickly sum up the business benefits, the next-gen data warehouse:

• Creates data-driven customer journey resulting in increased customer satisfaction

• Enhances business agility and faster time-to-market

• Enables and improves and faster decision making

• Reduces infrastructure, maintenance, and admin overhead costs, resulting in improved ROI

• Accesses and enables self-service business intelligence capabilities


With the evolution of data warehouses in the cloud, it is time to take away the complexity traditionally associated with business intelligence infrastructure and democratize data. Next-generation data warehouses have the ability to truly enable a big leap forward in enterprises, allowing on-demand access to make informed business decisions.

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