Data analysis and data security are two main challenges that organizations are currently facing. The rapid growth of data, its high variability and the lack of knowledge about its content can lead to high infrastructure costs and difficulties in complying with security regulations (GDPR).
In this digital age, we are generating more and more data, and innovation is needed to reduce the gap between generated and analyzed data.
The most advanced solutions in the market such as Artificial Intelligence or Machine Learning, are complex technologies that require advanced technical knowledge that is sometimes difficult to find internally in organizations.
Why should I make business decisions based on my data?
According to a Gartner study, by 2022 90% of corporations will explicitly mention data as a critical business asset and data analysis as a strategic differentiating action.
Making decisions based on the data generated is an increasingly popular practice (known as data driven decision making) because it helps organizations to generate new opportunities, increase revenues, predict trends in demand, optimize their processes and obtain relevant ideas for their business.
From operational excellence to data monetization
The data environment is complex, there is a large volume and an extensive list of sources. That’s why we must rely on data analytics tools to extract the maximum potential from the available information assets.
Available data sources
Data analytics add value to the business by:
- Cost optimization by predicting demand based on data from previous years
- Scalable and rapidly integrated data solutions that ensure business continuity in the face of sudden changes in market behaviour
- The application of augmented analytics for business process automation
- The quantification and assessment of metrics related to work performance facilitating better workforce management
Monetization of data
- Direct monetization
- Trading information
- Enhancing services
- Sale of data through data brokers
- Development and offer of data subscriptions
- Sell data analysis solutions where data is part of the final product
- Indirect monetization
- Improving efficiency
- Reduction of measurable risks
- Generate new products and markets
- Stronger partner relationships
Advanced analytics, the next wave of data disruption
Advanced data analysis leverages Machine Learning and AI techniques to transform the way data is developed, consumed and shared.
Some case studies of the use of these tools are:
- Data preparation: use of ML/IA to automate data evaluation and quality, speed up data processing, manipulation and cataloguing.
- BI (Business Intelligence) platforms: ML is applied to visualize and develop relevant conclusions extracted from the data without having to build models or write complex algorithms.
- Data Science: uses ML/IA to automate key aspects of data science such as data modeling (autoML).
Advanced analytics is changing the business approach to its customers by transforming three dimensions: market, organization, and capabilities.
Cloud Analytics, the cloud is the new enabler of data analytics
It had already become the reference platform for storing organizations’ data, and now it also enters strongly into data analysis, offering a wide portfolio of services and great benefits that make the cloud the best choice for data processing and analysis.
Cross integration of data, taking advantage of information from different parts of the organization through data analysis solutions.
Find answers and ideas for your business quickly
The cloud allows agile integration of your data, as well as an efficient identification of the important ideas to be taken into account in the decision-making process.
Unified data access
Centralization of data, allowing quick access to business data.
Scalability and agility
Cloud computing allows you to add storage and data analytics capabilities as needed.
Unique and protected access point to your data. It also facilitates the management of your data by controlling access to information.
The Cloud is a central platform for access and connection to your data, with high availability that will enhance collaboration in your organization.
Data analytics as a managed service, a simple but strategic decision
As we have seen there are several challenges that organizations are experiencing related to data analysis.
Addressing these challenges with the right service provider will help you maximize the value of your data and expand your business. The benefits of outsourcing data analytics to a service provider are numerous:
- Access to a broad portfolio of IT professionals when internal assignment is not possible
- Leverage the value of data for decision making
- Better market knowledge for specific business verticals
- Greater scalability and agility when it comes to responding quickly to customer needs
- Support and a better understanding of data protection and regulatory compliance