data literacy

Cyber threats types and sources

A cybersecurity threat is a malicious act that aims to damage or steal data and disrupt digital life in general. These threats include data breaches, computer viruses, distributed denial-of-service (DDoS) attacks, and other attack types. Cyber ​​threats also include obtaining unauthorized access to data, theft, damage or destruction of information technology resources, intellectual property and other forms of confidential information. Cyber ​​threats can come from within a company through trusted users, or from remote locations from unknown parties.

Sources of cyber threats can be:

Hostile Nation-States

National programs designed for cyberwar include cyber threats in the form of propaganda, website corruption, espionage, critical infrastructure destruction, and even death. The programs are state-sponsored and increasingly sophisticated, posing serious threats. Their active development can cause widespread and long-term damage to the national security of other countries.

Terrorist organizations

Terrorist organizations use cyberattacks to harm national interests. They use cyber defense systems less, which makes them more vulnerable. The threat of terrorist groups increases with the entry of a more competent generation into their ranks.

Corporate spies and organized crime

The main threat of corporate spies and organized crime lies in their ability to carry out industrial espionage in order to steal trade secrets or embezzle large amounts of money. The criminals’ main interest is in making a profit or disrupting the ability of the business to make a profit.


The main hacktivistsэ goal is to spread propaganda. They seek to support their political program.

Disgruntled Insider

Is a common source of cybercrime. Insiders do not need to have a high knowledge level to disclose confidential information, as they may have access to the data. Third party vendors and employees who inadvertently introduce malware into systems, upload sensitive data, and share it online also qualify as insider threats.


Cybercriminals can use a zero-day exploit to gain access to data. They also hack information systems to challenge or brag. Now, such attacks do not require a high level of knowledge and experience. Many automated attack scripts and protocols can be obtained from the Internet making it much easier to launch an attack.

Natural disasters

Natural disasters represent a cyber threat disrupting the infrastructure.

Random actions of authorized users

Incorrect S3 configuration by an authorized user can lead to data leakage. Some of the biggest data breaches were caused by bad configuration.

Major Cyber ​​Threats in 2021

Phishing attacks related to Covid-19

The attack was carried out using «harmless» emails or sites infected with malicious links. Interaction with such links will leak credentials. Because the topic of the pandemic aroused user interest and fear, the attacks had high success rates.

Insider threats

According to Verizon’s 2019 report, 57% of all database breaches were related to insider threats. Unfortunately, this type of cyber threat can’t be mitigated with a control strategy. To provide better protection against insider threats, it is worth restricting access to confidential information.

Ransomware attacks

This type of cyber threat is one of the most powerful. During such an attack sensitive data is encrypted by cybercriminals. It is possible to decrypt them only after paying the ransom.

Polyglot files

Such files may have multiple file type identifiers (for example, they may be classified as PPT and JS). Cybercriminals pack malicious code into a file, which helps bypass security controls.

DDoS attacks

As the adoption of IoT devices increases the risk of DoS attacks increases. The attack occurs because of sending many network requests from several compromised IoT devices to the site targets. As a result the servers are overloaded.


The attack occurs as a result of the introduction of malicious codes into advertising links. Such ads may be placed on sites that allow third-party advertising, even on social media feeds.

The Latin American Mlspadu is a prime example of an advertising attack. The malicious code was embedded in an advertising campaign for McDonald’s coupons on Facebook. While interacting with the ad a zip file was downloaded and installed on the user’s system, which contains a Trojan to steal banking credentials.

What is cybercrime?

Thanks to modern technologies information sharing between private and business users has become much easier and more convenient. But sometimes people trade convenience for privacy exchanging large amounts of corporate and personal information, paying with a single click, saving passwords etc. Such actions increase the risk of becoming a cybercriminals victim.

Cybercrime involves the use of computer technology to achieve illegal goals. This is any criminal activity that is related to a computer, network devices or network (fraud, data leakage, phishing attacks, clickjacking, typesquatting, DOS attack, etc.).

The main goal of cybercrime is the profit that cybercriminals will receive. However, the goal may also be to damage or disable computers and devices, use computers and networks to distribute malware, illegal information, videos, images and other materials, infect computers and networks with viruses. The «target audience» of cybercriminals can be both individuals (personal information) and organizations (corporate data). The large-scale transition of companies to a remote work mode due to the pandemic has contributed to an increase in cybercrimes number.

Although this type of crime does not affect the physical body of a person, it does affect the «digital body». In the digital age, each person is a set of numbers and identifiers in a multitude of databases owned by the government and various companies. This once again emphasizes the importance of networked computers in people’s lives.

One of the main features of cybercrime is its ubiquitous nature. Actions can take place in jurisdictions that are far away. This in turn entails serious problems for law enforcement agencies that require international cooperation.

Where does cybercrime take place?

All cybercrimes take place in cyberspace –  is a virtual world, an electronic environment. This space usually includes a large computer network and consists of many computer subnets. A key feature of cyberspace is an interactive and virtual environment for multiple participants.

5 common cybercrimes that affect individuals and businesses:

  1. Phishing Scams

91% of successful cyberattacks start with fear or interest in clicking on a link. Phishing emails mimic messages from a familiar person or trusted company. Their goal is to force a person to give up their personal data and follow a link that downloads a malicious program. About 1,000 phishing attacks are launched daily.

  1. Website spoofing

Website spoofing is a type of attack in where the site is as similar as possible to the real official site and makes users believe it. Fake sites use the name, corporate style, user interface. This makes them as believable as possible and forces users to enter logins and passwords. The purpose of the attack is to gain user trust, gain access to user systems, steal data, money, or distribute malware.

  1. Ransomware

Ransomware is a modern version of regular ransomware that has been around for a long time. How this virus works: criminals steal something of value, and demand payment for the return. For most organizations, this is about encrypting corporate data. A ransomware attack causes downtime and paralyzes the work of all employees.

Without restorable backups the company is effectively at the mercy of a cybercriminal. It will hold corporate data «hostage» until the organization redeems the decryption key. Ransomware has become one of the major problems and threats for organizations.

  1. Malware

It is specially designed software with the aim of gaining access to a computer or damaging it. The targets of a malware attack can be: power, influence, money, information. Recovery from this type of attack is usually time-consuming and costly.

Popular types of malware include:

  1. IoT hack

The Internet of Things provides access to everyday activities and business processes on the Internet. All Internet-connected entities collect and exchange data. Now data is one of the most valuable assets. It provokes hackers to constantly try to use all the devices that collect data.

Data Infrastructure and its key elements

Competent work with data brings business to a leading position. Incorporating data-driven innovation into operational business processes provides up-to-date information across all enterprise directions, leading to more efficient operations. During the 4th industrial revolution, data is the fuel for Artificial Intelligence, Machine Learning, robotics, the Internet of things, etc. According to forecasts, by 2025 the digital transformation wave will reach 3.7 trillion US dollars.

Data by itself has no value. It acquires value with the right working approach: having a data strategy, skills to work with it, a management process and an infrastructure that includes software and technical tools for collecting, storing, processing and transmitting data.

Although infrastructure is an important element of the data workflow, starting with infrastructure is not entirely correct. Sure, it will be necessary to invest into devices, applications, platforms and services that will provide efficient work with data. But the work begins with setting goals and developing a strategy, tailoring the tools to the strategy, challenges, and business issues.

With the increasing desire to capture data value and the growing demand for the technical means to enable it, the market for platform and solution providers has expanded significantly. This situation made it possible to reduce the entry barrier to work with advanced technologies and analytical solutions. Some of these offerings are called infrastructure as a service. Selecting the right product from a wide range of products requires doing a lot of research, understanding business needs, and identifying questions that need to be answered by introducing a new product.

Key functions that the infrastructure should provide:

  1. Data collection. Injecting internal (transactional data, customer feedback, cross-departmental data) and external data (data from social media, public sources, purchased third-party data) into the infrastructure stack. The process of collecting streaming data in real time must also be provided, which requires a reliable collection infrastructure.
  2. Data storage. Depending on data privacy level it’s possible to store it locally in own storage or in the cloud. Cloud storage providers provide free access to data for business users from anywhere. It also reduces the initial cost of setting up own servers, energy, and security.
  3. Data processing and analysis. At this stage work begins with machine learning, computer vision, speech processing, neural networks, etc. The main task here is to find a solution for preparing and cleaning data, building analytical models and extracting valuable information from unprocessed information.
  4. Obtaining information and disseminating it to business users. It is the stage of data visualization and reports creation with the help of which business users can make decisions, share information, improve internal processes efficiency, create improved products or services.

Qlik Enterprise Manager

Today every company has certain requirements for data processing. One of these requirements: the rapid  data and metadata integration in heterogeneous environments for analytics. Managing individual data streams across multiple endpoints can be quite inconvenient, inefficient, and time consuming. Qlik tools allow to centrally manage data pipelines at scale.

Qlik Enterprise Manager provides a control center for the tasks of setting up, running and monitoring replication and transformation throughout the enterprise. The tool provides an intuitive management interface for Qlik Data Integration. The graphical user interface simplifies the process of designing, executing and controlling Qlik Replicate and Qlik Compose tasks.


DataLabs is a Qlik Certified Partner. A high level of team competence and an individual approach allows to find a solution in any situation. You can get additional information by filling out the form at the link

Previous #fridaypost “Qlik Data Streaming”

How to get started with data?

Data has become one of the most important business assets for any size and activity company. At the moment, there are many data use cases. However, each company must choose its own option that will bring the greatest benefit. To be successful today all companies regardless of size or industry must have a data strategy. It is important to understand exactly what data is needed to achieve goals and improve business results.

With so many potential data use cases it’s easy to get confused. But the task of choosing a scenario should not be left to chance. Below are some tips to help leaders prioritize and create an effective enterprise data strategy.

  1. Brainstorm

First of all, it is necessary to outline the desired result: «What exactly does the business want to achieve?», «What are the key business tasks and goals?.

There are 4 main uses for data:

  1. Detailing use cases

Every data project that has been brainstormed needs to be drilled down:

  1. Define the use case

Having passed the previous stages, it is necessary to determine the most suitable for a particular business. This approach will identify data priorities, cross-cutting issues, requirements and goals. You should start with the current business strategy, the most significant challenges and opportunities. Depending on the ambition and scale of the data processing strategy, it is necessary to choose from 1 to 5 use cases. They will also be the most strategic and long-term ones.

After that, it is worth identifying 1 – 3 «quick goals» that can be achieved quickly and can show value. A quick result will demonstrate the effectiveness of the data processing strategy and allow to get team members’ support.

Business Intelligence is a tool for effective business performance

Business Intelligence is a set of methods and technologies for data collecting, processing and analyzing. BI connects business analytics, data visualization, data mining, infrastructure and data processing tools, technologies for making informed decisions. The tool allows to work with business activities data, obtain data on competitors, and determine market trends. This allows to make effective data-driven decision-making process, optimize all business processes, including customer experience and employee satisfaction improvement, ensure smooth efficient operations and increase revenue. Let’s take a look at exactly how Business Intelligence can help improve a business.

  1. Data driven decision making

Business Intelligence enables an efficient decision-making process by transforming disparate information into ready for analytics data. Access to up-to-date corporate information provides a prompt response to any events. Customer Relationship Management (CRM) solutions bridge the gap between staff and managers.

  1. Customer needs analysis

Along with active changes in the market, customers’ needs and interests are changing. Each client is looking for the best way to solve their problems. This influenced the growth in demand for embedded BI tools, in particular CRM. This system allows to study the client’s interaction process with a particular brand in real time, as well as to determine the best way to interact with a particular client. Analytical data also makes it easy to segment customers depending on their life cycle, set up individual interaction methods. This approach ensures optimal resources usage to attract new customers and maintain the current customer base. Moreover, Customer Relationship Management (CRM) solutions bridge the gap between staff and leaders.

  1. Improvement of market analysis effectiveness

Business Intelligence helps to get complete and up-to-date market information. Users have the opportunity to analyze data on shopping patterns, identify information about customers, their behavior, and predict market trends. This in turn contributes to more efficient planning of business activities.

  1. Effective business model

Working with all the data company owns, including marketing strategy, data on competitors, market, buying habits, and more allows to create a reliable and results-oriented business model.

  1. Sales strategy

To develop an individual sales strategy, it is important to study and understand information on sales volumes, annual turnover, competitors, trade policy, etc. BI tools used to study these indicators allow to plan lead cost, turnover, future growth, number of sales and develop an individual marketing plan.

  1. ROI on Marketing

Currently companies use many channels and ways to promote their product or service. BI tools provide an opportunity to calculate the ROI of a marketing initiative (email marketing, promotion in social networks, applications, Google Ads campaigns etc.) and determine the most effective marketing solutions and strategies.

  1. Mobile business intelligence

Getting up-to-date information is an important component of any modern business. Access to real-time data provides an opportunity to gain a competitive advantage. A fully integrated mobile business intelligence solution gives an access to the business information you need to make strategic decisions.

Database as a service

The active growth of the database sector was fueled by the emergence of Covid-19. To survive in the new environment, many companies have had to revise and improve their applications and digital services. As a result, more database instances were deployed, as well as tools to ensure quality data manipulation. Since no business plans to reduce data usage, there will be new products for data processing and ways to create value.

One of the main trends of 2022 is related to the company’s databases management. Not so long ago, all database instances had to be run inside a local data center. For now, developers and IT teams have more options. Together with an on-premises deployment, databases can be run by a service provider, deployed in the cloud, used as a service from a cloud provider, and run as serverless instances.

Database-as-a-Service (DBaaS)

Database-as-a-service supports more applications and digital services, so more companies will be migrating to this option in 2022. DBaaS is a cloud computing model that provides access to a database without installing hardware or software. Configuration and maintenance are the provider’s tasks, the user can immediately use the database. DBaaS is a fully managed service that includes software and hardware, backup, administration, networking, and security. The implementation of this tool ensures a fast, safe and cost-effective workflow that allows to optimize all business processes.

Database-as-a-service benefits:

Database-as-a-service disadvantages:

The main DBaaS disadvantage the lack of direct access to corporate information: the storage and processing of databases is transferred to a third party, which makes it impossible to influence security and recovery measures. However, the level of reliability, security and efficiency of DBaaS far exceeds standard databases.

The need for enterprises for stand-alone cloud databases is growing today. Cost reduction, availability, renewal, flexibility, efficiency are the main factors that drive companies to use DBaaS. The global cloud database and DBaaS market is projected to reach $ 399.5 billion by 2027.

Data as a key element of a decision-making process

Data is an integral part of modern life. Almost every human action generates large data amounts. The most valuable use of this data is how companies use it to make business decisions. For example, viewing candidates’ profiles on LinkedIn to recruit a targeted candidate, research and identification of priority markets for product promotion.

The most serious business data applications are automated and used to solve more complex and important tasks.

These processes take place automatically without human involvement.

Experience and intuition are traditional assistants to business leaders. However, despite the value of these qualities, a business using data in the decision-making process is 19 times more profitable. Data helps to make better business decisions that leads to goals achievement.

Many companies claim to be data-driven because it is «trendy» these days. But in practice this is not entirely true. They only take data into account if the data matches the beliefs and intuition of the business leader. A data driven business assumes that data is the only point of truth. Decision making of any complexity occurs as a result of data analysis.

There are 4 main areas where data is needed to make effective decisions:

  1. Solutions related to customers, markets and competitors

The data will help to understand better customer behavior, track changes in habits and interests, make a targeted offer, meet customer expectations and stay ahead of the competition.

  1. Financial decisions

The company’s management has the ability to investigate in detail sales trends, cash flow cycles, profit forecasts and changes in stock prices. This allows to make informed budget allocation decisions and leads to cost savings and growth.

  1. Decisions related to internal operating activities

The joint use of data and Artificial Intelligence allows to optimize the operation of equipment, set up the process of preventive maintenance. This will allow to determine in advance where breakdowns may occur, and repairs will be required. With this information it’s possible to plan the optimal replacement / repair process and minimize deadtime.

  1. Solutions related to human resources

The data helps to study the team composition and quality, to determine the shortage of certain specialists, qualifications level, the appropriateness of compensation for a certain type of work, since employees are always tempted to go to a competitor, taking their experience and skills with them. So, using the data, Google identified 8 basic qualities of a good manager, including «a good coach», «a clear vision of the team». This analysis allowed the management of the company to make informed decisions on the promotion of employees on the career ladder.

Key points in data strategy development

The modern world is developing and becoming smarter. At the same time, data is becoming a key tool for gaining a competitive advantage. The quality of data and analytics use, and the latest technologies introduction directly affects business competitiveness.

Data is a valuable business asset that transforms workflows. Almost every company, no matter the size, should be involved in data-related activities. In this case, each such company must have a clear and effective strategy for working with data.

It is essential to start working with data with a strategy. At the moment, part of the business and their leaders are simply collecting as much data as possible, because of the hype around Big Data. However, they do not think for what purpose they are doing it. The second part of the business is so overwhelmed by the data provided opportunities that they deliberately move away from solving this issue.

At the stage of developing a strategy, firstly it is important to understand what the company wants to achieve and what data can help to do it. It does not matter at all what data is already collected and is being collected now, what data are collected by competitors, what type of data is available. Data can only be useful if it meets specific business needs, helps achieve a goal, and thus creates value. Therefore, to avoid collecting useless for a particular business data, it’s necessary to focus on the goals, problems and issues that need to be solved with the help of the data.

Many companies use data processing strategies in areas of business such as marketing and sales. However, this is not enough – a plan is needed for the entire company. There is also a perception among executives that data and analytics are IT department’s responsibility. That is, managers are shifting responsibility to IT specialists. In fact, it doesn’t have to be that way. The responsibilities of IT technicians include storage, ownership, access, and data integrity based on strategic goals set by business leaders.

Key points in data strategy development:

  1. Data needs. To understand what data needs to be collected, first of all, it is necessary to determine what it is for. Different types of data may be needed for each specific purpose.
  2. Data searching and collecting process. When goals are defined, it’s possible to start thinking about finding and collecting suitable data. At the moment, there are many ways to do this: buying external data, using internal data, introducing new collection methods.
  3. How the collected data is transformed into analytic data? To extract business ideas, it’s necessary to understand the process of applying analytics to data.
  4. Requirements for technological infrastructure. The next step in the strategy development process is choosing the hardware and software that will enable an efficient data management process.
  5. The level of data expertise within the company. Getting the most out of the data requires certain knowledge and skills. This issue can be resolved with the help of internal resources of the company or the involvement of specialists from outside.
  6. Data governance. Working with data, especially personal data, presupposes strict adherence to the rules and regulations. It is critically important to consider and ensure security, privacy and data integrity when developing a strategy.

What’s the best way to start interacting with data?

High quality interaction with data is the market leaders’ hallmark. Data has become the foundation for groundbreaking concepts like Artificial Intelligence and the Internet of Things. The main goals of using data: products and services upgrade, internal processes optimization and performance improvement, understanding user needs and behavior, monetizing and additional revenue generating.

Everyone understands that it is necessary to work with data, but not everyone understands where to start. Any process should start with setting goals. Before you can start working with data and getting value, it’s necessary to establish long-term and short-term goals for the company (for example increase profits, scale, reduce customer churn and manufacturing defects, understanding customers and the market). Moreover, each team member must know and understand them.

Here are a few guidelines to help you identify a company’s capabilities using data:

  1. Use cases

An effective solution would be to familiarize yourself with existing cases and look at the other companies’ experience, how they used the data and what result was achieved. A great example is the American company Netflix, which has adopted data mining. The company uses the collected data on the behavior of their customers to form recommendations for films and shows, content, etc. With the help of data company monitors the quality of video playback and it helps to increase the customer service level. Also, Netflix monetizes the received data through advertising partners.

  1. Brainstorm

To solve the problem, it is necessary to gather all interested business participants and brainstorm the way. The purpose of this process is to combine business goals and possible use cases of data to achieve a result.

During the brainstorming process, it’s important to answer the following questions:

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