Data Analytics Services

The Data Analytics Tool provides insights into the business performance with a real-time dashboard. It effectively process the raw data and draw out valuable insights from the information. As raw data has significant potential, data analytics helps businesses to optimize their performance and improve their core. Organizations implement analytics to business data to identify, analyse and improve business performance.

Hadar Technologies had professional team members as a leading data analyst who assist in product development, analysing customer trends, and improve operational efficiency. Hadar Technologies provides key services in data analytics such as:

• • Marketing and Sales
• • Predictive Forecasting
• • Financial Services
• • E-commerce
• • Supply chain and production

Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data.

Data visualization in the context of BI often implies the interactivities through the software. By enabling users to interact with data, the software opens tremendous opportunities to view data in many different angles. It transforms the data visualization from a presentation technology to an analysis process.

Artificial Intelligence and Machine Learning are much trending and also confused terms nowadays. Machine Learning (ML) is a subset of Artificial Intelligence. ML is a science of designing and applying algorithms that are able to learn things from past cases. If some behaviour exists in past, then you may predict if or it can happen again. Means if there are no past cases then there is no prediction. ML can be applied to solve tough issues like credit card fraud detection, enable self-driving cars and face detection and recognition. ML uses complex algorithms that constantly iterate over large data sets, analysing the patterns in data and facilitating machines to respond different situations for which they have not been explicitly programmed. The machines learn from the history to produce reliable results.

The ML algorithms use Computer Science and Statistics to predict rational outputs.

There are 3 major areas of ML:

• • Supervised Learning
• • Unsupervised Learning
• • Reinforcement Learning

Data collection is defined as the procedure of collecting, measuring and analyzing accurate insights for research using standard validated techniques. A researcher can evaluate their hypothesis on the basis of collected data. In most cases, data collection is the primary and most important step for research, irrespective of the field of research. The approach of data collection is different for different fields of study, depending on the required information.

The most critical objective of data collection is ensuring that information-rich and reliable data is collected for statistical analysis so that data-driven decisions can be made for research.

Data Collection methods:

• • By Phone
• • In-Person Interviews
• • Mail Surveys
• • Phone Surveys
• • Web/Online Surveys
• • Interviews
• • Questionnaires and Surveys
• • Observations

Data quality management is a set of practices that aim at maintaining a high quality of information. DQM goes all the way from the acquisition of data and the implementation of advanced data processes, to an effective distribution of data. It also requires a managerial oversight of the information you have. Effective DQM is recognized as essential to any consistent data analysis, as the quality of data is crucial to derive actionable and - more importantly - accurate insights from your information. Data quality management provides a context-specific process for improving the fitness of data that’s used for analysis and decision making. The goal is to create insights into the health of that data using various processes and technologies on increasingly bigger and more complex data sets

Hadar Technologies also provides specialized training on Data Analytics to its customers using different analytics tools. So that you can grow your business through intelligent data collection and analysis. Learning Data Analytics is the measurement, collection, analysis and reporting of data. So that you can grow your business through intelligent data collection and analysis.

Data harmonization refers to all efforts to combine data from different sources and provide users with a comparable view of data from different studies.

Its service intends to merge distinct levels, genres and sources of data to ensure that data is comparable and compatible. Data Harmonization improves the quality and utility of master data through Data Cleansing and cataloguing disparate sources of data and provides an integrated picture of data. The data catalog merges all the specifics of organization's data assets using a technical dictionary with regimented classification templates and data requirements. And this enables the method of standardization for abbreviation and description generation.

Data migration is the process of selecting, preparing, extracting, and transforming data and permanently transferring it from one computer storage system to another Storage and cloud migrations sort of migrations ensure businesses with opportunities to increase their coordination, intensify growth, and discover business advantages. Data migration offers cost-effective transmission of applications to an upgraded and innovative context.