How to create customer-centric data platforms

It has become pivotal for data leaders to improve their data warehouse offerings to match fluctuating customer demands.

In an era where big data holds one of the largest monopolies in the enterprise, the data warehouse is heralded as the essential tool to manage these vast volumes of data.

Innovations in technology such as the IoT and mobile computing, and an organisational appetite to adopt these latest technologies, have all led to exponential data growth.

This has been equally matched by an increased desire for data-driven insight across the business, to help make more informed decisions and better respond to customers.

While data warehouses have been integral to accessing this data, clunky legacy on-premise systems or big data platforms have struggled to respond to the large volume of data produced, and to fluctuating customer demands.

>See also: Hadoop: the rise of the modern data lake platform

These platforms are often confined to limited user accessibility, are complex, and unable to provide real-time data – thus failing to provide the timely insights that businesses require.

Yet the introduction and integration of cloud into the data warehouse has negated these legacy issues and equipped organisations to navigate this modern landscape.

Tapping into the cloud

As more data is created than ever before, true cloud data warehouses have enabled instant access to data, ensuring no data-set is outdated before it’s even analysed.

Legacy data warehouses or big data platforms have primarily worked on an ETL (Extract, Transform and Load) model which has been largely awkward and delayed organisations’ access to data.

On the other hand, data warehouses built for the cloud are instead powered by an ELT (Extract, Load and Transform) process, quickly automating data and enabling up to fifty times faster processing. By seeing data instantly, organisations are in a better position to respond to their customers quickly.

Consumer healthcare search platform company, Amino, quickly reaped in the benefits of shifting from a legacy data platform to a true cloud data warehouse. Amino was responsible for handling data of 215 million people, 900,000 providers, and over five billion patient and doctor interactions.

Analysing this huge data set took a week on its existing legacy system, but since turning to the cloud, data processing times were reduced to less than an hour. With big data playing such a vital role in responding to Amino’s customers, accessing this data with minimal downtime was critical.

>See also: In-memory databases are essential for business

Another benefit of the cloud is its ability to support concurrent users. In today’s business world where multiple users require instant access, cloud based services such as Dropbox and Microsoft 365 are easing the ways in which people from around the enterprise can collaborate. No longer are employees restricted by location or time zone; they’re now able to tap into these online services to work together in real-time.

This also holds true for data analysis. Data is no longer accessed by a single individual. CIOs have acknowledged that in the face of large volumes of data production and growing business intelligence teams, supporting concurrent users is key.

Data warehouses architected for the cloud can very quickly make this a reality by instantly provisioning users’ access to data right at their fingertips. Legacy platforms, even those retrofitted to cope with cloud, will still suffer from user accessibility, leading to more delays in processing data.

Moving data between organisations

Traditionally, data generated and analysed would often be siloed to internal IT departments. But one of biggest advances made possible by the cloud is the ability for organisations to share datasets externally between partners and other business units, in a secure and governed manner.

Breaking down the barriers that exist with on premise solutions by sharing data between third parties will lead to easier collaboration between organisations, but also quicker business decisions.

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The ability to share data can result in a broader understanding of different data sets to better analyse new customer markets faster than ever before, as well as the opportunity to develop new or enhanced product offerings for customers.

In today’s fast-paced world, receiving accurate and real-time data is essential. Any delays to this process can put organisations at a real risk of failing to accurately and quickly respond to customer demands.

However, by rebuilding the data warehouse for the cloud, this new architecture enables direct access to any number of users, while allowing for the free sharing of data without boundaries – finally placing the customer at the heart of the data.


Sourced from Benoit Dageville, co-founder and chief technical officer, Snowflake Computing

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Nick Ismail

Nick Ismail is a former editor for Information Age (from 2018 to 2022) before moving on to become Global Head of Brand Journalism at HCLTech. He has a particular interest in smart technologies, AI and...