Our Comprehensive Data center solutions including transformation and systems management hosting and co-location services and building secure and energy efficient infrastructure environment.
The Telecommunications & Media, Banking & Financial Services, and Insurance and Health Care industries conduct a large number of paper-based transactions. In a data-driven, automated world, paper is still essential in processes that need to comply with regulations.
Data is one of your most valuable business assets. But like anything of value, it needs to be cared for and polished in order to keep it in good working order. Data cleansing from Al Faris enables you to protect the value of your data and ensure you gain maximum value from this prized asset.
Modeling and Algorithm
Data modeling is the process of learning about the data and developing a data model that combines events and in the process creates meaning. It’s common to join the events table with other data sets and aggregate these enriched events into smaller data sets.
A data product is the production output from a statistical analysis. Data products automate complex analysis tasks or use technology to expand the utility of a data informed model, algorithm or inference.
Collecting data for Market Research purposes can be difficult; hence, more and more businesses have been choosing to outsource data collection to research experts. Our tools and techniques are continuously developed and enhanced to meet the best practices and industry standards. Because of this vast experience and exposure in various industries, you can be assured that you can leave your Data Collection tasks to us.
From Research Management to Survey Design, from Data Collection to Data Processing, Infinit Datum can definitely take care of every step of your research process. Our team of Market Research professionals is trained to sift through any type of data, transforming them into meaningful insights that will aid your company into making the best possible business decisions.
Data collection services include research consultation, survey and questionnairedesign, data collection and data processing. Al Faris’s experienced and credible research team qualifies us to be an invaluable partner for your research and data collection projects:
Al Faris’s has over 10 years of research and data collection experience in the higher education and high school markets.Our experienced staff is trained in survey design, data collection, direct outreach, and database creation.We offer the flexibility and customization in the timeframe you require.
Al Faris’s Data Management Solutions offers an end-to-end data collection service including:
Analysis of data quality
Analysis of company wide data coverage and current consistency
Collection of prospective client’s current data points.
Complete data collection
Being familiar with data processing technologies, Al Faris specialists offer professional data processing solutions and services to IT companies and software vendors worldwide.
Our research and development teams have the experience and required expertise to provide custom data processing development for your projects. Accumulated best practices, research capabilities, an understanding of data formats as well as a host of implemented technologies allow our company to save your project money and accelerate delivery times.
Al Faris development team has an extensive data format library for desktop and mobile systems enabling advanced electronic data processing capabilities. Best practices and methods for data acquisition, transmission, protection, and recovery help , Al Faris teams to develop custom automatic data processing, data security and inspection solutions.
The Telecommunications & Media, Banking & Financial Services, and Insurance and health care industries conduct a large number of paper-based transactions. In a data-driven, automated world, paper is still essential in processes that need to comply with regulations and align with customer needs. But, paper impedes appropriate processing of data, restricts its transformation into information used in downstream processes and makes storage and retrieval of data difficult
We offer data processing services across industries including Telecommunications & Media, Banking & Financial Services, Insurance and health care with our right-shore delivery model to suit every client's need.
Our operational strategies are focused on maximizing efficiency and ensuring a better customer experience.
Clean, accurate data is essential when planning your marketing campaigns.
The Data Processing Company offers a range of data cleansing services and data management solutions.
Our data cleansing services include merging, migration, rebuilding, and de-duplication, and standardization, normalization, verifying, enriching & appending missing data. Expressed another way, we do whatever it takes to provide you with clean data. This solutions increase your organization’s ROI and productivity whilst reducing cost and wastage.
Data cleaning services include the process of detecting and correcting errors and inconsistencies from a data set in order to improve its quality. Data cleaning services aim not just to clean the data, but also to bring uniformity to different data sets that have been merged from other sources. After cleansing, a data set should be consistent with similar data sets within the system.
As a leader among cleansing companies in UAE, we provide a full suite of data cleansing services:
Import Data: Unclean data from your systems is imported into our cleansing system. Typically provided by yourselves in an Excel, CSV, or Tab-Separated Text file format.
Merge Data Sets: Data from multiple differently formatted sources (eg excel, csv, sql, sap, salesforce etc) is converted and merged into a common database.
Rebuild Missing Data: Wherever possible, missing information is recreated (e.g. Post codes, states, country, phone area codes, gender, web address from email addresses etc.).
Standardise Data: Data is combined, separated or modified to ensure that the same type of data exists in each column. This step ensures that your contact’s first name, last name, email address, mobile phone number etc. are all in their respective columns.
Normalise Data: Similar data is normalised (e.g. mister, Mr., mr are all converted to Mr. Or street, st., strt. are all converted to St.). Telephone numbers are converted to their standard Telstra format, or otherwise as advised by yourselves. Email and web addresses formats are also checked, where provided, and reformatted as necessary.
De-Duplicate data: We use a custom-built fuzzy-matching algorithm to identify potential duplicates. Our methodology provides high accuracy matches with a tolerance for misspelling, missing values or different address orders. For mission critical data, these results are manually reviewed (by either ourselves or our client) and the database updated accordingly.
Verify & Enrich Data: Data is validated against internal and external database sources and additional value-adding info is appended. (Eg business contacts can be validated against the White / Yellow pages to verify that their phone number and address are still current. ABNs, ANZSIC codes, credit ratings, geo-coords, key contacts, employee size, profit, revenue, time zones etc can also be returned for each company. Where databases are not available, we can provide call centre services to track down this hard-to-find data. Alternatively, we also we also provide self-verification services. See Data Check for more details.
Export Data: Data can be exported in numerous formats for example, excel, csv, SQL database, XML, tiff, PDF, or as required. Typically, we return it in the same layout and format that we receive it.
Modeling and Algorithm
The Data Modeling as a trade has been practiced in the IT world for many decades. As a concept, data model is a process to arrive at the diagram by exploring the data in question and getting a deep understanding of the data. The process to represent the data in a pictorial way helps the business and the technology experts to understand the data and also understand how it is going to get used. In addition, the relationships within data sets, which is pre-defined, determine in advance how the data should look like.
Data mining model algorithms provide the decision-making capabilities needed to classify, segment, associate and analyze data for the processing of data mining columns that provide predictive, variance, or probability information about the case set.
Many data mining algorithms are goal-oriented; given a case set, a data mining algorithm will predict something about the case, usually an attribute of the case itself. Most algorithms require a training set of cases where the attributes to be predicted are already known, at which point the algorithm constructs a data mining model capable of predicting these attributes for cases in which the attributes are unknown.
Each data mining algorithm is supported by a data mining algorithm provider, which is an OLE DB provider that supports the OLE DB for Data Mining specification. Because the needs and functions of each data mining algorithm provider are different, it may be necessary for a client application to first determine the capabilities of a data mining algorithm provider.
Data has become ubiquitous with the exponential growth of emerging digital technologies. Managing this burgeoning volume of data every day is the latest challenge for enterprises wanting to harness it for business value. Big Data is more than a factor of size; it opens a world of opportunities to find new and valuable insights from the myriad data sources, generating data at varying speeds and types.
Insurers are caught between the Internet and old trusted legacy systems. There is a pressure to provide information and transaction capabilities over the web for customers and agents to use the system conveniently. Maintaining multiple systems that have been added over the years is a maintenance headache. Daily batch jobs, multiple data entry and reconciliation requirements increase the overhead to a large extent.
We help you with the following:
Big Data Management
Big Data Technology Strategy Definition
Big Data Technology Use case Identification
Big Data Infrastructure Set-up and Management
Application Development and Maintenance
Big Data Analytics
Big Data Analytics Strategy Definition
Big Data Business Use-case Identification
Big Data Analytics Models / Framework: Development and Enhancement
Data analysis is nothing new. Even before computers were used, information gained in the course of business or other activities was reviewed with the aim of making those processes more efficient and more profitable. These were, of course, comparatively small-scale undertakings given the limitations posed by resources and manpower; analysis had to be manual and was slow by modern standards, but it was still worthwhile.
eDocs is a simply smarter way to manage content across the extended enterprise in a way that end users love and IT endorses.
eDocs is a web based document management application that uses standards and Open Source technologies.
Al Faris leverages its years of experience in the eLearning space and ready availability of domain experts to provide customized e learning and digital education solutions to help customer enhance their workforce performance and increase their customer satisfaction.
E-Commerce is no longer just about providing web-based services. It is about enabling retailers, brands and catalogers to be more consumer-centric across channels.
Internet Banking offers a host of services and facilities that give you real-time access to your account. You can make and receive payments to bank accounts and open Fixed and Recurring Deposits, view account details, request a check book and a lot more.