Introduction

The year 2022 ended being one of the most challenging years for global markets, especially for retail, industry, financial and insurance segments. Impacted by the rise in central bank interest rates, remnants of a pandemic that seems to have no end, and the beginning of an armed conflict putting at risk the stability in the purchase and sale of energy commodities, the year 2023 begins presenting itself as even more challenging than 2022.

The technology areas of retail companies, traditional industries, financial and insurance companies have already understood the importance of investing in data, integration and sustainment to achieve business results that ensure the survival of companies in a period with so many uncertainties.

In this article we bring a holistic view of the importance of these departments in each of the studied markets, as well as trends we will see become reality in 2023.

Data ÔÇô What is the data area?

The data area’s main objective is to ingest data from different sources to consolidate and treat them, generating metrics and KPIs relevant to the business. This is where the well-known Data Lakes emerge, infrastructures built for this purpose. Before talking about trends in data areas, it is important to bring the four pillars of this architecture:

Data sources

It is the set of sources that can generate data for the Data Lake. They can be structured data such as corporate databases or unstructured data such as social media information and analytics.

Storage and processing

ÔÇìData is processed and stored within the Data Lake. Here it is possible to create different data treatments and divide the Data Lake into layers so that cataloged and treated data serve different analyses and purposes. In this process, much of what is known as ETL ÔÇô Extract, Transform and Load is applied ÔÇô This is the name given to processes to transform data so that they can be used for business needs.ÔÇì

Advanced analytics

ÔÇìThis pillar implements advanced Machine Learning, artificial intelligence and statistics algorithms for more complex analyses such as behavior prediction models.

Business IntelligenceÔÇì

Data is consumed by analysis tools to generate reports, metrics, KPIs and serve as triggers for marketing actions, sales and backlog prioritization.

Why is the data area so strategic?

There are no arguments against data. Data-driven decision-making is much more assertive as it does not take into account assumptions and guesses, excluding biased and vitiated hypotheses, and giving way to real-time information that can generate knowledge and assertiveness in business decisions. A data strategy is a long-term plan that defines the technology, processes, people and rules necessary to manage an organization’s information assets. All types of companies collect large amounts of raw data and need to use it in their favor to ensure competitive advantages.

According to the study “Introduction to Data Mining” by FERRARI D.G., there is much to be explored in this area and your company needs to be aware of this, as we point out below:

• So far, 0.5% of available data have been used and analyzed in the world;
• Every second we do 40 thousand searches for information, which equals 3.5 million searches per day;
• Facebook users send 31.25 million messages and watch 2.77 million videos per minute;
• 90% of existing data in the world were created in the last two years;
• Companies that do data analysis are 5 times more likely to make decisions faster than their competitors;
• For a company on Forbes magazine’s most admired list, a mere 10% increase in data accessibility will result in more than $65 million;
• Every minute, 300 hours of video are uploaded, just on Youtube;
• The White House has already invested more than $200 million in big data projects.

The popularization of cloud computing also boosted the creation and structuring of Data Lakes. Clouds offer a series of services that make data ingestion and treatment simple, and even if there is no specialist within the project, it is possible to deliver projects using infrastructure and DevOps knowledge. Furthermore, the cost benefit of cloud storage can be advantageous, if well managed. This is because cloud storage has different costs per tiers, linked to how often data is accessed.

Data opportunities applied to Retail

In retail, an area of extreme competitiveness and low loyalty, understanding customer behavior to optimize their digital experience is more than necessary. Therefore, the creation of Data Lakes in retail is strategic to profile consumers and create personalized experiences. This strategy is endorsed by Gartner, in its retail trends report.

In the same report it is indicated that 65% of retail CIOs intend to invest in data analysis and business intelligence and 35% in artificial intelligence, with marketing and supply chain being the areas of greatest focus.

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­ƒÅåIf you are a technology leader in the retail segment, we invite you to discover the tech trends for the sector in 2023, by clicking here.

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Data opportunities applied to Industry

The industry is experiencing Industry 4.0, where the arrival of 5G, with reduced latency, enables and facilitates machine-to-machine communication in various scenarios that were previously not optimized. This is because 5G promises to reduce machine communication latency from 10 milliseconds to 1 millisecond, according to Teleco.

To give you an idea of the amount of data generated through IoT, a Boeing flying from Los Angeles to New York alone generates more than 2,499,841,200 terabytes of data.

In addition, it is believed that by 2025, Brazilians will have at least 7 machine-to-machine devices around them.

Data generated by sensors can provide valuable insights to engineers, indicate where to optimize costs and improve machine operation, and offer new revenue streams with repairs and maintenance of parts performed more intelligently. AWS has a page that indicates all the benefits of using data solutions focused on industry and the Internet of Things. 

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­ƒÅåIf you are a technology leader in the sector, we invite you to discover the tech trends for the sector in 2023, by clicking here.

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Data opportunities applied to Financial and Insurance

Insurance and financial segments tend to be more digitally mature compared to the markets mentioned above, and the range of data applications is extremely diverse given the varied departments that exist in these two areas.

Specifically in insurance, data analysis can be used to improve insurance pricing and be more assertive regarding monthly charges, premium costs, in addition to boosting cross-sell offerings by insurers.

In the financial area, the use of Big Data mainly helps in risk management and fraud prevention, using data to identify patterns and suspicious behaviors, outside the user’s routine.

OpenTudo: Global integration has already begun

In recent years we have seen initiatives like Open Banking and Open Insurance whose objective is to be APIs for open data sharing between financial institutions, in the first case, and insurance companies, in the second case. Brazil is a reference on this topic and is seen as the most complete model, created in less time and with greater applicability among countries that have already tried this initiative. With two successful models, it is expected that in the coming years, other sectors will join the “Open” initiatives and are markets to watch. See some:

Open Education

ÔÇìAt the last APIX 2022, the world’s largest API event, a panel was held just to talk about integration in educational systems. In this panel, open education emerged as a theme to make it possible for the MEC to centralize a student’s information with data from different educational institutions. There are already initial platforms like the Student Journey app whose objective is to show the entire study history of a student, centralized in a single application.

Open Health

ÔÇìThe Open Health initiative already has an official website where you can follow the initiative’s newsletter. Following the same logic as Open Banking, the objective of Open Health is to share clinical data to facilitate access to patient history and facilitate portability between health plans. 

Open Investment

ÔÇìAnother front in which Brazil is a pioneer, Open Investment will be treated as the fourth phase of Open Banking and will bring the option to share data on investment funds, CDBs/RDBs, LCIs, LCAs, CRIs, CRAs, Debentures, stocks, ETFs and treasury bonds. The scope proposal is led by Anbima.

IT Sustainment ÔÇô Operating structure and important terms

IT sustainment is the work that supports the entire IT infrastructure, whether software, hardware or even network. A sustainment cell is composed of Analysts who work at different service levels, according to the detail and specificity of the problem.

The first level (N1) handles the simplest and easiest calls to resolve. If the problem is more complex, the call is forwarded to a second level (N2). At this level, a deeper investigation of the problem is carried out. If the resolution is very difficult and requires very specialized knowledge, the call may be forwarded to a third level (N3) of service.

The management, prioritization and routing of calls between levels is agreed upon in a document called SLA ÔÇô Service Level Agreement. It is in this document that it states how calls are prioritized and how long they must be resolved.

To ensure proper SLA execution, the sustainment team may follow IT governance and process management methodologies. The most well-known methodology is ITIL ÔÇô Information Technology Infrastructure Library ÔÇô which is a collection of best practices for processes, deliveries and communication. ITIL is based on four dimensions of action: Processes, People, Products and Partners. From these dimensions, 34 management practices are extracted.

To facilitate the sustainment team’s work, it is quite common to use APM ÔÇô Application Performance Monitoring tools. These tools help easily identify which infrastructure component is problematic and provide dashboards and metrics for monitoring platform availability. The three leading APM platforms in the market according to Gartner’s magic quadrant are Datadog, Dynatrace and New Relic. 

Sustainment ÔÇô Strategic vision

It is estimated that 40 to 90% of a platform’s costs are generated after its launch. This is because maintaining platform availability tends to be a complex challenge. In this scenario, it is extremely important that a company maintains a sustainment team to avoid unavailability on its platform, which causes enormous negative impacts. The main impacts of an unavailable platform are:

Financial losses

ÔÇìA Forrester magazine study shows that financial damages caused by one hour of downtime (system unavailability) can range from 1 to 10 million dollars.

Reputation loss

ÔÇìThe company’s image is harmed when a downtime is perceived. For the customer, the experience is strongly impacted when they are executing a journey and it is abruptly interrupted because the system goes down.

Revenue loss

ÔÇìWith a platform down, revenue drops as customers cannot complete their journeys, which often involve financial transactions.

Productivity loss

ÔÇìSystem downtime can also affect employee productivity, who are unable to perform their work if a system they use goes down. This also impacts team engagement, who feel less motivated to work in an environment with instabilities.

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Main Skills in Sustainment

These roles and skills are strategic for the success of a sustainment team:

Sustainment Analyst

ÔÇìRole responsible for handling N1 and N2 calls. A professional with technical competencies directed at infrastructure, security and networks.

DevOps

ÔÇìThese are roles directed at people to implement the DevOps culture on the platform. He will be responsible for automating processes with the objective of facilitating problem identification and acting proactively in mitigating risks and unavailability bugs. His technical competencies involve knowledge in shell script, Infrastructure as Code and CI/CD pipeline structuring.

SRE (Site Reliability Engineer)

ÔÇìSRE is a role that connects with the development team and operations team to apply practices that ensure scalability, predictability and platform stability. SRE has a set of technical competencies related to observability, infrastructure and platform security.

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How can Zappts help with your IT operations?

Companies like BTG, Santander, Getnet, PagoNxt, Auttar and Porto trust their consulting and technological development processes with Zappts. Since 2014, Zappts has been delivering business results through technology, delivering high-relevance cases using agile processes, software development best practices and quality, and unparalleled ability to understand and solve the day-to-day pains of technology development projects.

We contemplate solutions for all phases of digital solution development, from discovery processes to solution sustainment. With defined processes and agile management, our deliveries are always based on expectation alignment, quality and technical robustness. Contact our specialists and learn more.

Contact us here and guarantee your free assessment now!

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