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Automl aka Automated Machine Learning, is a cutting-edge technology that aims to empower users to easily and efficiently build powerful machine learning models without requiring extensive expertise in data science or programming.

By automating the time-consuming and complex tasks involved in machine learning, such as algorithm selection, hyperparameter tuning, and feature engineering, Automl democratizes the field, enabling non-experts to leverage the benefits of machine learning in their business or research projects.

By streamlining the process, Automl not only saves time and resources but also enables users to make informed decisions based on accurate and reliable predictions, ultimately driving innovation and unlocking new possibilities in various domains.

The Internet of Things (IoT) refers to the interconnection of everyday objects and devices through the Internet, allowing them to collect, store, and share data.

This revolutionary concept has transformed the way we live and interact with technology.

By enabling seamless communication between devices, IoT has led to the development of smart homes, smart cities, and even smart industries.

From controlling household appliances with a smartphone to monitoring energy consumption in real-time, IoT has the potential to enhance efficiency, convenience, and sustainability in various aspects of our lives.

By leveraging the potential of IoT responsibly, we can harness its power to create a more connected and intelligent world.

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DataOps is an emerging practice that combines the principles of agile development, DevOps, and data management to streamline and accelerate the entire data lifecycle.

It focuses on collaboration, automation, and efficiency to ensure the smooth flow of data from ingestion to delivery, enabling organizations to make data-driven decisions faster.

By applying DataOps strategies, businesses can improve data quality, reduce time-to-insight, and increase the agility of their data teams.

Data Operations, the innovative approach breaks down the silos between data engineers, data scientists, and other stakeholders, promoting cross-functional collaboration and enabling organizations to unlock the true value of their data assets.

Data lineage refers to the documentation and tracking of the origin, life cycle, and movement of data throughout an organization.

It provides crucial insights into the data's source, transformations, and usage, helping organizations ensure data accuracy, compliance, and trustworthiness.

With data lineage, organizations can trace data from its inception, understand how it has been altered or aggregated, and identify any potential issues or dependencies.

By maintaining a comprehensive data lineage, organizations can enhance data governance, facilitate data quality management, and optimize decision-making processes based on reliable and transparent data sources.

Data Mart

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Schema mapping

Data Virtualization: A technology that allows data to be accessed and integrated from multiple sources without physically moving or replicating the data

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Data governance refers to the overall management and control of an organization's data assets.

It involves defining and implementing policies, procedures, and practices to ensure the accuracy, completeness, security, and availability of data.

By establishing a framework for data governance, organizations can effectively manage and utilize their data resources, making informed decisions and improving overall operational efficiency.

Data governance ensures compliance with regulatory requirements and safeguards sensitive information, fostering trust and transparency among stakeholders.

An effective data governance strategy enables organizations to harness the true value of their data, leading to improved decision-making, competitive advantage, and long-term success.

Master data management

DATA CLEANSING

The act of bringing together data from different sources into a single location or database

Data replication is a crucial process in the field of data management, involving the duplication of data across multiple storage locations or systems. This practice ensures that valuable data is readily available, even in the event of system failures or network disruptions. By replicating data, organizations can improve data availability and access, enhance system performance, and ensure data integrity. Additionally, data replication is also vital for supporting business continuity and disaster recovery efforts, as it enables rapid recovery and reduces downtime. Data replication plays a vital role in modern data management, providing organizations with the security and reliability necessary to effectively utilize and protect their valuable information.

Data federation is the process of combining data from multiple sources into a single, virtual database, providing users with a unified view of the information. This approach allows organizations to access and analyze data from various systems without the need for data duplication or complex data integration efforts. By utilizing data federation, businesses can achieve a more comprehensive view of their operations, enable better decision-making, and enhance the overall efficiency of their data management processes. Furthermore, data federation promotes flexibility and scalability, as it allows for the inclusion of new data sources or modification of existing ones without disrupting the overall architecture. Data federation empowers organizations to leverage their data assets more effectively and efficiently, ultimately driving business growth and success.

Data integration is the process of combining and harmonizing data from various sources into a unified and structured format. It involves extracting, transforming, and loading data in order to provide a comprehensive view and enable meaningful analysis. By integrating data, organizations can eliminate data silos, improve data quality and consistency, and make informed decisions based on a holistic understanding of their data. In today's data-driven world, data integration plays a crucial role in enabling organizations to unlock valuable insights, drive innovation, and gain a competitive edge.

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- Extract Transform Load

Extract refers to the process of pulling data from a source such as an SQL or NoSQL database, an XML file or a cloud platform.

Transform refers to the process of converting the format or structure of a data set to match that of a target system. Load refers to the process of placing a data set into a target system.

ETL uses a set of business rules to clean and organize raw data and prepare it for storage, data analytics, and machine learning (ML).

* ETL optimizes repetitive data processing activities for more efficient analysis.
* ETL tools can automate the data migration process and incorporate data updates on a regular or on-demand basis.
* ETL will allow data engineers to spend less time on mundane activities like data movement and transformation.

HOTO Flashlight Lite

This compact flashlight became an instant favorite of ours by offering an impossibly elegant aluminum build, incredible versatility, excellent battery life, and a USB-C connector for recharging it. Thanks to a bundled light diffuser, the gadget can quickly transform from a high-powered flashlight with stellar zoom capabilities to a lamp for use while camping or on the road.

SonicBrush

The SonicBrush is marketed as the world’s first fully automated toothbrush – meaning you don’t even have to move it around your mouth to get a perfect clean. Because it brushes every tooth in your mouth simultaneously, the manufacturers claim it can reduce the time we need to spend brushing our teeth from two minutes to just 30 seconds.

Gocycle G4

The Gocycle G4 is a luxury folding e-bike that's brilliantly designed; the components are beautifully made and the overall effect is one of dazzling style. The folding mechanism is a breeze to operate

Chatbot

Chatbotis a computer program that simulates human conversation through voice commands or text chats or both. Chatbot, short for chatterbot, is an artificial intelligence (AI) feature that can be embedded and used through any major messaging application

Augmented reality (AR) and virtual reality (VR)

Augmented reality and virtual reality have the potential to enhance the user experience in various fields, including gaming, education, training and entertainment. Users can interact with digital things in the actual world using AR technology, for instance, and can completely immerse themselves in a virtual environment using VR technology.

HyperAutomation

HyperAutomation involves the use of multiple technologies like Artificial intelligence, Machine Learning, and Automation technologies such as Robotic Process Automation, Natural Language Processing to automate as many business processes as possible.

Machine learning

Machine learning is a growing technology which enables computers to learn automatically from past data. Machine learning uses various algorithms for building mathematical models and making predictions using historical data or information. Currently, it is being used for various tasks such as image recognition, speech recognition, email filtering, Facebook auto-tagging, recommender system, and many more.

5G networks

The next generation of wireless networks, or 5G networks, offers higher speed and reduced latency than 4G networks. They have the potential to enable new applications like remote surgery and smart transportation systems.

Genomics

Edge Computing

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Robotics Process Automation

is a natural language processing tool driven by technology that allows you to have human-like conversations and much more with the . The language model can answer questions and you with like composing , essays, and code.