Data Analytics

Why cloud-based data & analytics platforms are so attractive for companies

For many companies, flexible access, rapid structuring and speedy analysis of business-relevant data is becoming increasingly important. The topics of data analysis and cloud technologies can be found everywhere, but how can they be combined advantageously? Is the cloud the right place for your data and analyses? And is it the right place for your organisation to get the most out of your data?

By Ahadi Schabnam, Data ＆ Analytics Consultant

Data is a driving force in today's business world, as well as an important corporate asset. Important insights are gained from data, which can deliver significant added value for the company and its customers. In order to gain these insights, almost all companies already carry out data analyses in one form or another. Some work with Excel spreadsheets to create trends and graphical analyses. Others use relational or non-relational databases or a data warehouse, which enables centralised data storage. Some companies already operate their own data analysis infrastructures in a company's own data centre (so-called "on-premise"). However, with the increase in data volumes, companies are facing a major challenge in terms of processing and evaluating data, which is why many organisations are now re-evaluating their infrastructure. Today and in the future, companies are dependent on intelligent and more powerful data and analysis platforms.

What goal are the companies pursuing?

We present in the Data & Analytics When working with our customers, the Swisscom team realises time and again that they are looking for a solution to a specific operational problem. The technology used to achieve this solution is secondary. Our customers need analysis platforms that are tailored to their needs so that they can realise their data-based use cases and projects.

In most cases, however, the needs cannot be solved by using an isolated data source. To get a complete picture of the entire organisation, companies need to connect their data sources and analyse them in a coordinated manner. Breaking down silos and implementing a centralised repository, the "single source of truth", leads to more efficient processing of complex requests and a better basis for decision-making and higher customer satisfaction. It is no longer enough to carry out the relevant analyses on a quarterly or annual basis. In order to increase the direct benefit, such analyses should be automated and carried out on a daily basis - or even in (near) real time.

The challenge of on-premise data and analyses

One of the most fundamental decisions that needs to be made is whether you want to build your data platform on-premise or in the cloud.

Setting up and operating a data centre and handling the volumes of data generated, as well as data integration requirements, involves considerable administrative effort and a large budget. Although the infrastructures are mature and can be operated stably, they cannot always keep pace with complex business scenarios that encompass several business areas or data domains. The right equipment must be selected and the appropriate knowledge and experience must be available for installation and management. The hardware has a certain lifespan and you will then be forced to replace your hardware. The hardware grows with the company and will certainly need to be upgraded many times. The different generations also increase the operating costs and very often the systems will need to be optimised.

The cloud is not just hot air, but offers clear advantages

The most obvious reason for the strong growth and advantage of cloud analytics is that it reduces upfront costs and shortens implementation time. Services are easily accessible via the web browser and billing is based on consumption through the "pay-as-you-go" business model, also known as the "OpEx model". Just like your electricity bill, your bill varies each month by the amount you use. The potential savings can vary from company to company and must be identified by comparing expenditure. Internet of Things (IoT) is one of the most common drivers for organisations embarking on the cloud transformation journey. On the one hand, a cloud infrastructure simplifies the connection of globally distributed devices to the services for end customers; on the other hand, the scalable, automatable and cost-effective device management connection also enables efficient management and maintenance of the devices.

As the cloud can support a virtually unlimited volume of data, cloud analytics platforms are highly scalable without long lead times or operational interruptions. Elasticity should also be mentioned here, as cloud services have the ability to adapt quickly to changing situations. With the help of the cloud, peak loads, which typically occur at the end of the quarter or in year-end processing, can be intercepted and the necessary analyses delivered in good time. The cloud provides the resources required for the current task and can also cope with high loads for short periods of time. However, unlike on-premise systems, the additional capacity can also be removed when it is no longer needed and therefore does not put a strain on the company's budget.

Another advantage of the cloud is its accessibility via the internet, which enables the entire organisation to access the same platform via a common interface. This promotes collaboration and a data-driven culture and also relieves the burden on the IT department, which was previously responsible for managing and providing data. The cloud also makes it easy for companies to experiment with the capabilities of artificial intelligence, including machine learning, to optimise analyses. This gives companies a number of other advantages. Machine learning achieves these benefits by finding patterns in company data sets and calculating possible outcomes.

Reservations about the cloud

Companies sometimes spend large sums of money on developing and improving their operating processes. This makes it difficult to abandon the existing infrastructure that has been expanded over the years and the associated investments and development work. Introducing a new technology can be very stressful for everyone involved and requires a well-thought-out strategy. There are also many organisations that persist with old technologies because they are not broken - so why fix or replace them? It's important to remember that not all data needs to be moved to the cloud in one go, as a 'lift and shift' migration where existing systems are moved to the cloud virtually unchanged can bring additional costs and challenges that are usually underestimated. Ideally, a cloud migration should be an agile process. A gradual replacement of existing systems and transfer to a new cloud-based infrastructure enables a smoother migration and gradual further development and optimisation of analyses. The step-by-step approach also provides sufficient time to optimally implement the systems set up in the cloud according to the latest findings, while data protection and data security is an issue that every company working with cloud technologies must be aware of. The use of cloud technologies is often rejected because data losses have been reported by other companies. However, the cloud is no less secure than a data centre outsourced to an IT service provider, provided the necessary precautions are taken and adhered to.

When it comes to data security (backups), the cloud makes it easier to prevent serious failures. If local backups are kept in the same building as the physical infrastructure, devastating data loss, for example in the event of a serious fire, is almost inevitable. Migrating to the cloud makes it easy to move backups to another data centre, reducing the likelihood of a serious outage. Of course, this additional protection is not free, but the shorter lead time and elimination of hardware investments mean that it can be implemented much more quickly.

When it comes to data protection, i.e. preventing unauthorised access and the outflow of stored information, the same principles must be followed as for an on-premise installation. Access must be restricted and the data must be protected against unauthorised use. The European General Data Protection Regulation (GDPR) and the Swiss Data Protection Act require at least encryption of the stored data for personal and health data (PII, PHI). Always remember that the cloud service provider (e.g. Microsoft Azure) is responsible for the availability of the platform. However, the customer is always responsible for protecting the data processed on it. However, with the correct configuration of the available mechanisms, this protection can be adequately implemented.

Digital transformation is an opportunity for your future

Many cloud platforms require employees to be trained beforehand in order to achieve the desired goal. Setting up cloud technology is usually part of a targeted digital transformation that takes some time. However, the performance, elasticity, scalability and security with which these products are introduced and the reduced costs, which are tailored to your needs, can make up for these disadvantages.

Every company can utilise the various benefits of such systems. The right cloud strategy can fundamentally change the way a company operates. However, this will not happen overnight. The key is to approach a well-planned, gradual transition and to be aware of the pros and cons.

Is the cloud the right place for your data and analyses? And is it the right place for your organisation to get the most out of your data?

We are convinced that many organisations are still unable to assess the benefits they can generate for their customers with modern analytics platforms and how they can generate additional revenue. We at Swisscom's Data and Analytics team will help you answer these questions, address your specific challenges and guide you on your transformation journey. Contact us to start your cloud experience now and our experts will use cutting-edge technologies and years of experience to help you develop a data and analytics solution and see your data from a new perspective.

Ahadi Schabnam

Ahadi Schabnam

Data ＆ Analytics Consultant

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