Nov 06
1

Data Deduplication

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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.

Nov 06
1

Career

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Data Analyst (02)


We are looking to add a rockstar Data Analyst to our team. If you have background working with large data sets, build model using machine learning and artificial intelligence, we would like to hear from.

What you will do:

  • Design metrics with the help of the senior data analysts, build reports and dashboards to better understand the user journey, monitor business health, and access data insights
  • Utilize quantitative techniques to test hypotheses and analyze the impact of product updates
  • Contribute to the design of internal procedures and partner with engineering to improve data consistency, cleanliness, and ease of use
What you bring to the table:
  • SQL knowledge
  • 2+ years of work experience in data analysis with SQL
  • Experience using statistical analysis and modeling techniques
  • Experience with BI tools such as Tableau, Looker, Power BI
  • Experience working with Big Data is a plus

Send your resume to info@eriq.ai

Nov 06
0

Data Analysis

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Data analysis using machine learning is a process of using algorithms and statistical models to automatically identify patterns and insights in large datasets. Machine learning is a subfield of AI that focuses on the development of algorithms and models that can learn from data and make predictions or decisions without being explicitly programmed.

The data analysis process using machine learning can be divided into several stages:

  • Data preprocessing: This step involves cleaning, transforming, and preparing the data for analysis.
  • Feature selection and engineering: This step involves selecting relevant features and creating new features from the existing data that can improve the performance of the machine learning models.
  • Model selection and training: This step involves selecting an appropriate machine learning model and training it on the preprocessed data.
  • Evaluation and fine-tuning: This step involves evaluating the performance of the trained model on a separate dataset and fine-tuning it to improve its performance.
  • Deployment: This step involves deploying the trained model into a production environment, where it can be used to make predictions or decisions on new data.

Machine learning models can be used for various tasks such as classification, regression, clustering, and anomaly detection. They can be used in various industries such as finance, healthcare, marketing, and transportation to extract insights and predictions that can drive business decisions.

Data analysis using machine learning can be applied to both structured and unstructured data, and the results can be used to improve the performance of decision-making systems, automate repetitive tasks, and identify patterns that would be difficult to detect manually.

Nov 06
0

Technical Consultation

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The goal of technical consultation is to help clients understand, plan, design, implement, and maintain technical systems and solutions that meet their needs and objectives. Technical consultants can provide a wide range of services, such as:

  • Assessing and analyzing the client’s current technical systems and identifying areas for improvement
  • Providing expert advice and guidance on technology selection, implementation, and deployment
  • Designing and developing technical solutions, such as software, hardware, and network systems
  • Providing training and support to clients on the use and maintenance of technical systems
  • Managing and coordinating technical projects on behalf of clients
Nov 06
0

Management

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ERIQ Inc., offers a dynamic and fast paced working environment, where creative thinking is encouraged and results rewarded. We constantly strive for excellence and continue to grow through hiring the very best people from some of the best universities in the United States. Team members grow in their expertise through in-depth training in advanced technologies, mentoring, teaming and challenging assignments. One of the secrets behind our success has been a motivated team which prides itself on enthusiasm, dedication and commitment.

We are committed to delivering products and services free of defects. Our total quality management (TQM) system recognizes the importance of people, culture and process management, the critical challenges in software development. A core element of the ERIQ culture is continuous improvements in our TQM system.

The methodologies used within ERIQ have developed over time through a combination of industry standards, academic research and intense experience. Joint Application Development (JAD) and Rapid Application Development (RAD) techniques are the foundation to these methodologies. The combination of these approaches focuses the team on the functionality with the highest business value, delivering it as quickly as possible. Our methodologies include:

  • Requirements analysis
  • Design and architecture
  • Software development
  • Testing
  • Documentation
  • Deployment
  • Maintenance

Project and program managers monitor schedules, as well as issues and risks that may impact the cost, quality or timeliness of the solution. Our project management methodology ensures involvement of key stakeholders from beginning to end so that final deliverables meet defined specifications and expectations. Deviations from planned activities are brought to the customer’s attention for guidance. In addition to software engineering processes, the company has predefined procedures for customer interaction as well as for post implementation support including bug fixes, enhancement requests and consultancy support services.

Nov 06
0

ChatBOT

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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.
Nov 06
0

Social Sentiment Analysis

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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.

Nov 06
0

About ERIQ

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ERIQ Inc., – Entity Resolution and Information Quality, was founded in 2021 with the objective of introducing artificial intelligence and machine learning technology for large scale data analysis, natural language processing in order to improve business productivity, decrease costs and improve profitability.

ERIQ Inc., is a privately owned company headquartered in Silicon Valley, California, USA. Several software and services businesses were started by the management team in 2004 and beyond, eventually leading to a consolidated company that was incorporated in 2021. The executive leadership team has extensive and diverse business experience in software, business development, and operations, delivering solutions in a wide variety of industries, both small and large including eCommerce and e-business, computer software and technology, banking, financial services, biotechnology pharmaceuticals, healthcare, telecommunications, retail, aerospace, education, and manufacturing. This real-world experience is supported by university-based academic research and study, along with key industry trends and forecasts by Gartner and Forrester Research.

Company Philosophy

Customers are not interested in technology, they are interested in solutions. We strive to make technology irrelevant to our customers so they can focus exclusively on their business needs. You simply tell us the “what” and we take care of the “how”. Our unique products and services remove technology, resource burdens and other hurdles, enabling you to move at the pace of your business. You think it and we do it.

We apply the right mix of:

- Vision to identify the right opportunities to best serve its customers
- Leadership to organize and manage the right resources to deliver on time and within budget
- People, the best and the brightest
- Process, including project and program management best practices, software reuse,  and a software development lifecycle precisely tuned to the problem at hand
- Technology, the right skills and tools

This comprehensive structure and attention to the many components required for success is a key factor that differentiates us.