Data deduplication is a process of identifying and removing duplicated data, in order to reduce the amount of storage space required. This is done by identifying and eliminating copies of identical data, while leaving a single unique instance of the data.

The process of data deduplication can be performed at different levels and in different ways, including:

• File-level deduplication, which compares files byte-by-byte and eliminates duplicate files.
• Block-level deduplication, which breaks files into smaller blocks of data and compares them to identify and eliminate duplicates.
• Source-based deduplication, which eliminates duplicate data at the source, such as at the server or client.
• Target-based deduplication, which eliminates duplicate data at the target, such as in a backup or storage system.

Data deduplication can be performed on various types of data, such as text, images, audio, and video files, and can be applied to both structured and unstructured data.

Data deduplication can be done through software and hardware, and it is often used in Backup and Archiving, Cloud Storage, and virtualization. Data deduplication can result in significant storage cost savings and can improve the performance and efficiency of data backup and recovery operations.

The data de-duplication process is particularly challenging when organizations operate in countries with different languages and multiple time zones. Data de-duplication requires attention to detail and advanced data Management. To meet these challenges, our team of experienced big data management specialists can help you streamline the data de-duplication process.

Our ISO-certified outsourcing experts have helped many global clients. Our specialized data de-duplication services eliminate redundant data and improve data quality in all file formats and computer systems – including databases (digital, online and offline), omni-channel retailing data, social media data, point of sale systems and CRM data (both cloud-based and in-house systems). We provide data de-duplication services that include data purging, data comparison, data integration, database de-duplicating, data matching and data merging.

Chatbots can be integrated with various communication channels such as text, voice, and messaging platforms, such as websites, mobile apps, and messaging apps like Facebook Messenger, WhatsApp, and Slack.

Chatbots can perform a wide range of functions, such as answering questions, providing customer service, making recommendations, and completing transactions. They are also used in various industries, such as e-commerce, banking, healthcare, and education.

There are different types of chatbots based on the technology used to build them:

• Rule-based chatbots: These chatbots use a set of predefined rules to determine the next step in the conversation, based on the user’s input.
• Self-learning chatbots: These chatbots use machine learning algorithms to improve their performance over time, by learning from the interactions with users.
• Hybrid chatbots: These chatbots combine the features of both rule-based and self-learning chatbots, to provide a more human-like conversation experience.

Social sentiment analysis is the use of natural language processing (NLP) and machine learning techniques to identify and extract subjective information from social media and other online sources. The goal of sentiment analysis is to determine the attitude, opinions, and emotions of the author or speaker towards a particular topic or product.

Sentiment analysis can be applied to various forms of digital content, including text, images, and videos, and can be used to extract valuable insights from large amounts of data. The AI-based sentiment analysis models are trained on large datasets of labeled text data and are capable of identifying patterns and features that indicate the sentiment of the text.

Sentiment analysis can be used in a variety of applications such as:

• Market research and customer feedback analysis
• Brand monitoring and reputation management
• Public opinion monitoring and political campaign analysis
• Product and service reviews analysis

It can also be used in business to understand customer engagement and feedback in real-time, which can be used to improve products and services, customer support, and overall customer experience.