VPC (virtual private cloud) stands for virtual private cloud. A VPC is a personal and private virtual network space located in a public cloud environment.

The main tasks of data analysts are to collect, process and analyze data, as well as prepare reports that can consist of graphs, diagrams, tables and other visuals.

Mixed workload is the capacity to support multiple applications with different SLAs in a single environment.

Database management system (DBMS) is software in which data is stored and managed in a secure, fast and easily accessible way.

Agile Project Management is a way of working that allows you to deliver a project throughout its entire lifecycle.

Algorithm is mathematical logic or a set of rules used to perform calculations.

Apache Hive is an open source data warehouse infrastructure that provides tools for data summarization, querying, and analysis.

Artificial intelligence refers to machine simulations programmed to mimic human intelligence, thought structure, and actions.

Automated machine learning, called AutoML (Automated Machine Learning) in the field of artificial intelligence and machine learning, describes integrated software platforms for the creation, training and optimization of a machine learning model.

Behavior analysis is a type of data analysis that tries to understand how and why people behave that way.

Big data is very large unstructured or structured data and is the most complex to analyze. For this you need advanced big data technology and big data tools that can work with large amounts of unstructured data. The amount of data collected is constantly increasing.

Business intelligence (BI) is the process and methods that enable organizations to generate more meaningful results and make data-driven decisions using tools such as data mining, data visualization, business analytics on existing data so that they can make better decisions.

Taking care of your customers is always the right strategy and a good way to do business. In this way, you can not only reduce your new purchase costs, but also increase your profits.

Cascading is a platform for developing big data applications on Hadoop.

Cloud computing is a system that allows you to rent your information technology infrastructure from a service provider instead of buying it.

Cluster analysis or clustering is a statistical classification technique or activity that involves grouping a set of objects or data in such a way that those contained in the same group (cluster) are similar to each other but different from those in the other group.

Comparative analysis means the comparison of two or more processes, document, dataset, or other objects. Pattern analysis, filtering, and decision tree analytics are types of comparative analysis.

Connectivity analytics is an emerging discipline that helps to explore the interrelated connections and effects between people, products, processes, machines, and systems within a network by mapping these connections and continuously monitoring the interactions between them.

Correlation analysis refers to the application of statistical analysis and other mathematical techniques to evaluate or measure the relationships between variables.

Customer churn rate is a business measurement that reflects the percentage of customers who end their relationship with a company within a certain period of time. This time period can be measured monthly, quarterly or annually, depending on the industry and product.

Customer experience, by definition, refers to all interactions between a brand and that brand's customers.

Data analysis is the thorough and careful review and interpretation of data collected through a study. Data analysis then yields results that can be used to accurately answer research questions.

Data anonymization techniques are the modification of data in systems in such a way as to prevent the data from pointing to a specific individual while maintaining the format and consistency of the data.

Data architecture is a set of rules, policies, standards, and models that govern and determine the type of data collected, and show how this data is used, stored, managed, and integrated within an enterprise and database systems.

Data cleanup, or data rubbing, is the process of detecting and correcting or removing data or records that are incorrect from a database. It also includes correcting or removing unformatted or duplicate data or records.

Data governance ensures that your data is consistent, reliable, accurate, and trusted in data-driven retrieval processes.

Data gravity occurs when the volume of data in a warehouse increases and the number of uses also increases. In some cases, copying or moving data can be troublesome and expensive. Therefore, data tends to pull services, applications and other data into its warehouse.

Data integration is a complex process by which data from different data sources and IT systems of a company is combined, enhanced, enriched and cleaned

Data Latency is the ability to load and update data in near-real time, while supporting query workloads at the same time.

Data literacy is the ability to read, evaluate, discuss and work with data/information. It can also be defined as a skill that enables everyone to ask the right questions, gather information, evaluate, and communicate effectively with others.

Data management is the implementation of policies and procedures that enable organizations to have control over business-critical data.

Data Mart is a slice of the data warehouse logical model that serves a narrow group of users. Many data subsets only need a subset of data from the full tables in the data warehouse.

Data matching is the process of linking a data field from one source to a data field from another source.

Data mining is ultimately the process of analyzing hidden data patterns according to different perspectives for grouping useful information, collected and consolidated in common areas such as data warehouses, data mining algorithms, facilitating business decision-making, and other information requirements, in order to reduce costs and increase profits.

Data Modelling means data analysis in its simplest form. It is one of the best ways to understand, store and manage data. It is made by data scientists and modelers.

The concept of making money from data refers to businesses making money in creative ways from data obtained on a daily basis in recent years.

Data Observability is the ability to monitor, diagnose, and manage the quality of data throughout the data lifecycle. It is also the discipline to automatically find out the health of your data and solve problems as soon as possible.

It is difficult to make a clear definition of data quality. The truth is that your data quality is good if the data achieves its purpose of using it. For example, showing the right values on a management board to guide the organization ensures that management is also consistent and the process is managed correctly.

Data replication is the process of moving data from one place to another, copying it, or storing data in more than one place at the same time.

Data science is about gaining actionable insights into the data a company owns, supported by a variety of applications.

Data security refers to the process of protecting corporate data and preventing data loss through unauthorized access.

Data virtualization is the reproduction of real data in a virtual environment. In this way, tests, experiments and analyses performed when working with real data can be carried out without compromising the accuracy and security of the real data.

Data visualization makes it possible to quickly obtain information by visualizing data regardless of format, type or source. It also allows the presentation of information that is not visible at first glance about what the data means in a clear and clear way.

Explore the evolving world of Data Warehouse Modernization and its importance in leveraging big data. Learn how data warehouses work, their types, requirements in various industries, and application areas.

This process, known as database shrinking, is a form of compression. It is intended to reduce the overall space without interfering with the data.

Deep learning, also known as deep neural learning or deep neural network, is an artificial intelligence (AI) function that mimics the way the human brain works to process data and create patterns that facilitate decision-making.

Demand forecasts help make the right business decisions by predicting future demands for products and services. Demand forecasts cover finely detailed data, historical sales data, surveys and more.

Descriptive analysis is the analysis of historical data to determine what is, what has changed, and what patterns can be identified.

DevOps brings people, processes and technologies together to deliver continuous value to customers. DevOps, a combination of the words dev (development) and ops (operations), is a software development method in which development and management activities are linked.

The concept of digital transformation has been supported by many industry experts since 2012, allowing companies to update their business models. Technologies such as data analytics tools, artificial intelligence and cloud computing services are contributing to the development of digital transformation in companies.

Dirty data refers to data that is wrong for a company. This inaccuracy not only means that the data is not correct, the correct data can also be “dirty”.

ELT is the initials of the words “extract, load, and transform.” Indicates a data integration process that extracts, uploads, and transforms data from one or more sources into a repository such as a data warehouse or data lake.

It is a three-step integration process used by companies to combine and synthesize raw data from many data sources into a data warehouse, data lake, data warehouse, relational database, or other application.

It places analytics into a workflow or application at the point of need and allows users to take immediate action without having to leave the app to gain more information to make a decision.

The word encode has meanings such as “encoding”, "encryption" or “symbolization” and basically involves the conversion of signals and data according to certain rules.

Financial analytics, also known as financial analytics, provides different perspectives on financial data related to a particular business, providing insights that will facilitate strategic decisions and actions that will improve the overall performance of the business.

GPT-3 is a more remarkable updated version of GPT, with more creativity and image recognition, while GPT-3 is quite popular due to possibilities related to data, language, and writing.

Generative AI is a type of artificial intelligence that generates content based on the information it acquires while learning. This technology uses advanced algorithms and models to mimic human creativity.

Collects, processes, and displays geographic information system data and images, including GPS and satellite imagery, in order to create geographic models and data images for more accurate modeling and forecasting of trends.

Hadoop is a distributed data management platform or open source recovery framework used to store and process big data. Sometimes it can also be described as a reduced distributed operating system.

MLOps is, in simple terms, a set of applications aimed at improving communication and collaboration between your employees in data science and operations of your brand. Machine learning is also defined as a combination of data engineering and development activities.

TechTarget defines machine learning as: “... it is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed.

Master Data Management (MDM) provides a unified view of data across multiple systems to meet the analytics needs of a global enterprise. Whether MDM identifies customers, products, suppliers, locations, or other important attributes, MDM creates single images of master and reference data.

Meta Data is data that describes other data in a structured, consistent form, so that large amounts of data can be collected, stored, and analyzed over time.

MongoDB is a cross-platform, open-source database that uses a document-oriented data model rather than a relational database structure based on a traditional table.

Natural language processing (NLP), a branch of artificial intelligence, addresses the understanding of human language (both in written and spoken form) by computers.

No code is the next step in the stable completion of the development of intelligent software and application solutions. The development method also allows process specialists who develop without using code but have no IT background or expertise to design applications and software.

NoSQL is an acronym and does not only mean Structured Query Language. Je diferencia de SQL es que datos estructurados no está archiviado en este base de datos.

Business Flexibility is the ability of a business to continue operating in the event of an outage.

Pattern recognition occurs when an algorithm places iterations or regularities within large datasets or into different datasets.

Predictive analysis is the analysis of big data to make predictions and determine the likelihood of future outcomes, trends, or events occurring.

Predictive maintenance is a method used to predict and prevent possible malfunctions in equipment. Using technologies such as sensors, artificial intelligence and machine learning, it constantly monitors the state of the machine and can pre-determine any problems.

Predictive analysis, a type or extension of predictive analysis, is used to recommend or predict certain actions when certain information states are reached or conditions are met.

Product lifecycle management refers to the examination of a product as it goes through certain stages of its lifecycle.

Python is an object-oriented, high-level programming language developed by Guido van Rossum. It first appeared in 1991. Designed to be both easy and fun, the name “Python” is a greeting to the British comedy group Monty Python.

R is an open source programming language used for statistical analysis. Includes a command-line interface and various graphical interfaces.

It can be defined in the form of enterprise marketing technology that provides contextually relevant experiences, value and benefit at an appropriate moment in the customer's lifecycle through preferred customer touchpoints.

Retail analytics is the analysis of data generated by retail transactions in order to make profitable business decisions.

Risk management, sometimes referred to as risk mitigation, is the process of developing a strategy to reduce certain individual risks until the aggregate risk level for an activity is reduced to an acceptable level.

Run-time or run-time computing refers to the type of computing in which multiple computing tasks occur simultaneously or at overlapping times

As its full name suggests (Structured Query Language), SQL is responsible for querying and modifying information stored in a specific database management system.

Explore the world of self-service analytics, explore its definition, interaction with big data a self-service business intelligence, and its numerous advantages. Learn how self-service analytics democratizes data and enables businesses to make data-driven decisions quickly and independently

Semi-structured data is data that is not captured or formatted by traditional methods.

Emotion analysis is the capture and monitoring of ideas, feelings, or feelings expressed by customers who have had various types of interactions, such as social media posts, customer service calls, and surveys.

Structured data are datasets with strong and consistent organization. Structured data is managed with structured query language (SQL), where users can easily search and edit data.

Supply chain management refers to the optimization of the flow from the supply of raw materials of a product to its production, from the logistics process to its delivery to the final customer.

Unstructured data is unfiltered information to which a fixed editing policy is not applied. It is often referred to as raw data.

Zero-based budgeting is an effective tool for organizations to control costs, manage resources, improve business processes, and improve performance.

A Business Continuity Plan (BCP) is a detailed document that shows how a business will continue to operate in the event of an unplanned interruption in service.

What exactly is the cloud server of choice to improve on-premises processes and provide convenience to all departments, what flexibility and benefits can it offer companies? Why is it so important? Let's take a look at all the curiosities about cloud server together.

Customer Data Platform (CDP) is a type of bundled software that creates a consistent and unified database that can access other systems.

A data warehouse (often abbreviated as DW or DWH) is a centralized “data warehouse” capable of integrating a variety of sources. It provides a separate environment from operational systems.

Discover the power of the Data and Analytics Roadmap and learn how to guide your organization's journey to a data-driven future. Discover what a Data Roadmap is, its benefits, how to create it, and why it's vital to your business success.

The classic definition of a digital twin is: “A digital twin is a virtual model designed to accurately reflect a physical object.”

Hybrid cloud is a combination of on-premises and cloud usage. Whether an organization's resources include on-premises, private, public, or multi-cloud, the hybrid cloud ecosystem offers the best in the world.

The logical analysis platform is a feature-rich technology solution designed to meet the needs of large enterprises.

A relational database consists of tables that are related to each other, and each table contains data of a specific data type - an entity. The relational model defines reality and usually has as separate tables as the number of entities. A relational database attempts to display all data items only once.

The data lake is where long-term data containers gather that capture, clean, and explore any raw data format at scale. Data subsets are powered by low-cost technologies that many downstream possibilities can benefit from, including data warehouses, and recommendation engines.

Active Data Warehouse (ADW) is a combination of products, features, services, and business partnerships that support Active Business Intelligence business strategy.

You can find all the details that need to be known about the computing cycle in the continuation of the article, and you can get healthy data by processing your company data according to these stages.