Innovative Solution for Data Analysis
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Data Science

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains.

Data Visualization

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 Warehousing

The data warehouse (DWH) is a repository of an organization's electronically stored data extracted from operational systems and made available for ad-hoc queries and scheduled reporting. In contrast, the process of building a data warehouse entails constructing and using a data model that can quickly generate insights.

Data Logging

Data logging is the process of collecting and storing data over a period of time in order to analyze specific trends or record the data-based events/actions of a system, network or IT environment.

Data Analytics

Data analytics is the science of analyzing raw data to make conclusions about that information. Many of the techniques and processes of data analytics have been automated into mechanical processes and algorithms that work over raw data for human consumption.

Data Migration

Data migration is the process of moving data from one location to another, one format to another, or one application to another. Generally, this is the result of introducing a new system or location for the data.

Augmented Reality for data analysis

Augmented Reality analytics measure the outreach and customer engagement levels of the AR campaign or solution.

Ai Based process
  • Internet AI. This is the simplest stage of AI. …
  • Business AI. Business AI has a limited memory. …
  • Perception AI. This is the first step into the “future of AI.” A key feature of this perceptive form of AI is the ability to compile and draw from past experiences, much like humans do. …
  • Autonomous AI.
Real time research & data analysis

Real-time analytics is the discipline that applies logic and mathematics to data to provide insights for making better decisions quickly. For some use cases, real time simply means the analytics is completed within a few seconds or minutes after the arrival of new data.

Ai Based process
  • Step 1: Build the foundation. You must start by preparing your data and applications to migrate to the right multicloud and data architecture environments. …
  • Step 2: Modernize the data architecture. …
  • Step 3: Set the stage for more innovation. …
  • Step 4: Build intelligent applications.
Data Visualization & Demonstration
Data visualization helps to tell stories by curating data into a form easier to understand, highlighting the trends and outliers. A good visualization tells a story, removing the noise from data and highlighting the useful information.
Ai Based process
  1. Step 1: Define a clear purpose.
  2. Step 2: Know your audience.
  3. Step 3: Keep visualizations simple.
  4. Step 4: Choose the right visual.
  5. Step 5: Make sure your visualizations are inclusive.
  6. Step 6: Provide context.
  7. Step 7: Make it actionable.
How do we do it
Our consultants are experienced analysts with statistical skills who have been Minitab® users and trainers for many years, as well as process and business improvement experts. Starting with your datasets, we can provide comprehensive analysis and reporting, as well as coaching and “challenge review” on previous analysis.
If you are at an earlier stage, we can advise on Voice of Customer techniques, Validation of the measuring Process, sample sizing, Operational Definitions, and mistake proofing your data collection.
This work can be done remotely or on-site in collaboration with your staff.

Why do Data Analysis Services help our clients?

The ability to access data skills on demand from a pool of experienced practitioners allows an organisation to provide insight quickly without the time and cost associated with developing and maintaining an in-house capability. Our consultants also provide an external perspective and benchmark based on their extensive consulting work experience, which adds extra value and robustness to the analysis and reporting produced versus output from in-house resources.
We frequently find that those gathering data lack the expertise to analyse it, while those analysing it have no knowledge of how it was gathered! Because our consultants do both, they can provide organisations with a one-of-a-kind end-to-end knowledge and ability.
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