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Data is the most valuable resource. It's more important than dollars, gold, and oil. The thing is that data can produce more business value than all these material things combined. Moreover, with the rise of Big Data, companies can move aside from focus groups, extrapolations, and assumptions. Instead, they analyze giant data sets with info about customers, markets, and competitors. Big Data is the primary driver of business transformation now. 

In the article, we will answer why the data-based business building is a must nowadays. We also will review the main features of transformation services with Big Data technology, core processes, and ways to handle them efficiently.

The Concept of Digital Transformation

Firstly, let's understand what does the term digital transformation mean. While there are different definitions, we prefer sticking to the simplest one: major changes that lead to work organization around digital technologies. For some brands, it starts with moving from paper-based accounting to electronic registries. For others, it's about cloud migration, data-first strategies, and active adoption of innovations. 

However, for all businesses, this transformation is essential due to three factors:

1. It leads to a single and clear vision. Big Data enables better insights into customer behavior that allow businesses to develop a more precise strategy. This also leads to improvements in customer service, better engagement, and retention. 

2. It offers better risk mitigation. Thanks to advanced AI-based analytics, companies can drastically reduce the number of data-related errors. Combined convenience and market insights result in more effective risk assessment strategies. 

3. It optimizes analytical processes. Evidently, larger data sets processed with advanced tools like cloud analytics often cut research budget and time expenses. Respectively, internal processes become smoother, new values arise.  

Four Benefits of Big Data for Businesses

Apart from core principles that fit nearly every company, there are a few less distinct advantages of Big Data implementation. In this section, we pay closer attention to the capabilities of data-focused analytical groups. The catch is that Big Data itself is pretty useless. Instead, being combined with powerful analytics, it can generate useful insights.

In this case, the benefits and new opportunities are as follows:

• Complete customer profile. Data flows from different sources such as social media, websites, phones, IoT gadgets, search engines, personal messages, and more. By gathering it, businesses can understand their clients better. Moreover, they can improve product/service delivery thanks to new info. 

• One repository - one strategy. As we've mentioned, data comes from various platforms. In traditional companies, it means that each department has access to a specific part of data but doesn't have a big picture. With centralized Big Data analysis, all teams can benefit from it, improving performance.

• Predictive analytics. What's the next step after learning everything about your user? Well, you should predict behavior. Big Data allows moving from responsive services to predictive alternatives that offer exactly what a customer wants. Just don't forget about GDPR when implementing this feature. 

• Unique user experience. The combined benefits result in one fantastic thing: data-driven businesses offer the best customer experience. They know what a client wants, they can sell it, they foster personalization. People appreciate such an approach because they want to feel valued and important for any brand. 

At this moment, stop reading and think about your business (existing or potential). Most likely, it has its own unique goals and expected results. While the mentioned benefits are universal, you shouldn't blindly trust them. As well, don't think about Big Data or analytics as a one-size-fits-all technology. Companies are different, so we can't guarantee that this particular strategy will work for your team. Always mind your differences. 

Now, as you realized the importance of tailored solutions, let's proceed to the idea of digital transformation backed by Big Data. 

Evolution Through Big Data

Last year, IDC released its Big Data and Analytics Spending Guide. Researchers projected that the global revenue of this industry would reach $275 billion by 2022, with IT and business services accounting for more than half of this sum. Just compare the number with almost $190 billion in revenue if 2019.

While the recent COVID-19 crisis affected (and continues affecting) all industries, including Big Data, this sector has good chances to flourish. Companies will try to recover, increasing investments in cost-effective market strategies. Undoubtedly, data science will define business development soon. 

That's why it's a great idea to start adopting Big Data and advanced analytics today. For companies that begin their journey and want to analyze the current state, IDC has a convenient tool called the MaturityScape. It defines five data/analytics progress stages:

1. Ad Hoc. Companies start initiatives occasionally, for irregular specific goals. There are no clear roles, deployment strategies, and measurements. 

2. Opportunistic. While the business has a much clearer vision of Big Data opportunities and models, there are still imperfect project management approaches.

3. Repeatable. Big Data strategies exist for different goals and in different teams. Managers can allocate resources wisely, on a regular basis. 

4. Managed. The strategies, tools, and goals match the global enterprise vision. Data and analytics become essential elements, ROI increases significantly. 

5. Optimized. A company has its own center of excellence in Big Data, disrupts the market, and focuses on more innovative approaches for even better value generation. 

Depending on your stage, you should focus on different development goals. Nevertheless, mature businesses already have established strategies. Hence, we want to provide a few insights for newcomers - teams that want to start working with Big Data. 

Make the First Step!

Overall, any company can start its data-focused analytics campaign. But not all companies need it. That's why your first stage should include proper planning. Be sure to identify the goals and keep them precise. Say "get 1,000 new subscribers till the end of April" instead of "attract customers" or "improve revenue by 25% in Q2 2020" instead of "earn more". 

The next step is to find appropriate data. Start with your CRM or ERP solutions, connect social media with analytical tools. If you have KPIs and result metrics, rely on them. It's important to know that initial data is unstructured and raw, so it can't be used to generate insights. Make sure to cleanse it and then pass to analysts. 

Finally, make the most out of this information. Collect, transform, save, and analyze. At the end of the day, you want to get clear and understandable reports that show how you can improve business operations and achieve the initial goals.