6 trends that are revolutionising data analytics

Business Intelligence

Changes in Information Technology are taking place at a dizzying pace. The cloud is monopolising nearly all the innovation, bringing about fundamental change in the way in which we conceive of IT infrastructures for modern businesses, and, therefore, how we go about managing one of the main assets of any organisation: data. In this article, we are going to break down the 6 key trends that are revolutionising data analytics.

The constant and variable collection of data made possible by the new IoT, the pressure for real-time analytics, predictive analytics and the application of AI in all aspects of our daily and professional lives. At a point when the internet revolution seemed to have passed its peak, it is time for the data revolution and its accompanying analytics. What are the trends that revolve around this revolution? We will take a closer look straightawy. Let’s get started!

Keys to understanding the present and future of data analytics

1. Cloud computing goes beyond cost savings: more analytics and Artificial Intelligence

The first wave of migration to the cloud was driven by applications as a service (SaaS), which gave companies the tools to more quickly and securely develop specific applications, such as CRM solutions. Later, the second generation saw many companies modernising their infrastructure in order to avoid having to maintain their own physical data centres (Iaas and PaaS).

Undoubtedly, these advances have been truly useful for all types of organisations, but with the changes we have experienced in 2020, the third phase will mean a truly crucial digital transformation for companies of any sector and size. Both data analytics and Artificial Intelligence / Machine Learning (AI / ML) play an important role in everyday business processes. We hope to see its accelerated adoption in 2021.

2. Regulatory compliance remains the driver of change

The transition to the cloud has a lot to do with both accessibility and control of data, addressing critical factors such as security and privacy.

Regulatory compliance is sometimes driving the impulse to move to the cloud, in cases where local infrastructures are required to change in order to adapt to current regulations. This is because the cloud is already offering the de facto solution: to be compliant with the rules that regulate business activity.

Therefore, the transition to the cloud continues to be a trend for 2021 owing to pure necessity for many. Specifically, Google Cloud is a platform built from the ground up based on these fundamental requirements, so that organisations of all sizes and industries can transition to the cloud with the assurance that data will be protected and the business will comply with the law.

3. Open infrastructures will reign and the multicloud will continue to grow.

According to IDC Research Spain, it is expected that in 2022 40% of core IT spending will be related to Cloud computing and that this percentage will increase to 80% in 2028.

This year, it is expected that 80% of companies, or perhaps even more, will adopt a hybrid or multicloud IT strategy. According to IDC, the percentage of companies that have more than one cloud provider has increased by almost 20 percentage points in the last 3 years, combining technology and business needs with cost optimisation or regulatory compliance.

This growth is normal, because companies want freedom of choice when it comes to moving their workloads. Infrastructures and open APIs are the way to go, because no company can afford to have their data locked on a specific provider or service.

It is now possible to quickly interconnect multi-cloud and on-premises data sources, obtaining specific benefits from each cloud as if it were a single infrastructure. And in parallel, this commitment to open standards and the cloud is adding greater value to data and analytical capacity. Open infrastructures allow us to choose the cloud modality that works best for our company.

4. Harnessing the power of AI / ML will no longer require a data science degree

Data science, with all the experience and specialised tools that have normally been involved, can no longer be the domain of just a privileged few. Members of the entire organisation need access to the power of data science, to be able to take advantage of capabilities such as Machine Learning (ML) and Artificial Intelligence (AI) modelling, without having to learn an entirely new discipline. By giving them this ability, they will improve their professional skills and their decision making. If they haven’t been consuming data so far, there is no doubt that they will.

By empowering the entire team with the power of analytics, companies will be able to collect, analyse, and act on data much faster than those still using the traditional model of data science in isolation. This improves productivity and informed decision making, and also frees up data scientists to focus on tasks more suited to their skills and training, rather than continually gathering, analysing, and creating presentations for their peers.

With the Google Cloud infrastructure and its data, AI and ML solutions, it’s easy to move your data to the cloud and start analysing it. Solutions and tools like Connected Sheets, Data QnA, and Looker make data analytics something that all employees can do, regardless of whether they are certified data scientists or analysts.

5. The data economy requires both real time and predictive processing

We are rapidly reaching a point where data residing in the cloud outstrips that which resides in data centres. By 2025, global data is expected to grow 61% to 175 zettabytes.

The real challenge is to extract value from the data in the moment. Analysing data from the past provides us with relevant information, but there are more and more use cases that require information in real time, especially when it comes to reacting to unexpected events. For example, identifying and stopping a security breach in the network in the moment, thanks to data analysed in real time. That moment can save countless hours and mitigation costs.

This is the same method that Google uses to help its customers overcome DDOS attacks. And if 2020 has taught us anything, it’s that businesses will need this ability to respond instantly to unexpected problems more than ever.

While real-time analysis of historical data has many benefits and competitive advantages, we must not forget the important role that predictive analytics can play. Traditionally, the data collected came only from the physical world, which means that the only way to plan what was going to happen was to look at what could be physically proven. But with predictive models and AI / ML tools like BigQuery ML, organisations can perform simulations based on real-life scenarios and information, which provides them with data on circumstances that would be difficult, expensive, or even impossible to test in physical environments.

6. More than 50% of Data Lakes will span multiple clouds and on-premises storage systems

At Intelligence Partner we are aware that aligning the appropriate services with each use case is not an easy task. While the cloud opens up numerous opportunities to improve options in terms of data management, the fact that so many companies are switching to these cloud solutions means that organisations will need a strong digital strategy if they are to remain competitive. And this, of course, applies to the way you think about your data storage.

Many companies are choosing the multi-cloud scenario for the flexibility of being able to choose from so many options à la carte. In the cloud, data storage has taken the form of Data Warehouses – which mainly store structured data so that everything is easily consumable – or Data Lakes – which bring together all a company’s the data, regardless of its internal structure.

The trend towards Data Lakes will grow this year, resulting in the line that separates a Data Lake from a Data Warehouse becoming increasingly blurred.Google Cloud has a variety of Data Lakes modernisation solutions that offer organisations not only the ability to integrate unstructured data, but also to use AI / ML solutions to facilitate navigation through the Data Lakes, thus driving information and collaboration.

From trend to reality

Assimilating all or some of these trends in any organisation is not an easy task. Although we are convinced that this is the way to go. The best way to take this path is to ensure you choose the right travel companions. Here at Intelligence Partner, we would be delighted to accompany you on your journey. Our specialisation and commitment to the services of theGoogle Cloud Platform place us in a privileged position.

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