Data-Driven Schools: A Framework to find measurable deliverables
This article aims to equip educational stakeholders with the knowledge that data can transform educational outcomes. It highlights the importance...
Utilise the power of Generative AI technologies to transform your business. We help our clients to productionize Large Language Models into their applications. Our team of experts help organizations on Generative AI POCs and guide them to integrate Gen AI features in the product.
Transform your organization’s data silos into a centralized data repository and get a 360-degree view of the entire organization. Our approach towards data engineering covers all aspects of data transformation, including, data lake, data warehouse, and data marts.
Data Science and Advanced Analytics bring out hidden patterns from the data, generating useful insights. Utilise these to derive insights from unstructured and structured data, assisting to make sense of all the data your business has gathered over the years, and leverage to solve complex business problems.
Closely working with the companies and providing data solutions, consulting rightly to enable the company to be data driven. Solution engineers work to balance many different aspects of the project, from data governance to design of data application.
Providing an end-to-end machine learning development process to design, build and manage reproducible, testable, and evolvable ML-powered software.
Leverage clarity of meaningful data through functional representation with interactive app and dashboard designs. With functional representation of data, we enable our clients to arrive at the right takeaways critical to their goals.
Empowering global businesses through data-driven innovation for sustainable growth and boundless opportunities.
To transform the Data and AI landscape as a leading Research and Consulting firm.
When it comes to data and analytics tools, we have the experience needed to transform your existing investments and help you add to your stack intelligently. We’ll help you assemble the full data puzzle. We arm you with everything you need to get the most out of your data stack.We take the stress out of selecting the components of your modern data stack. Our team of data experts will partner with you to design and implement data infrastructure that works for your business. We have extensive experience working in all the leading cloud data tools.
We have strong principles and a long history of delivering effective data solutions.
Data mining involves the analysis of large sets of data to produce meaningful information. Experts in this specialization apply statistics and predictive models to reveal patterns, trends, and correlations in data. This information can be used to predict future outcomes and to develop business solutions.
You can picture a data science team as a relay race, where a data engineer hands off the baton to a data scientist. Data engineers build and maintain frameworks that transform data into a format that is useful for analysis. This involves consolidating, cleansing, and structuring data from different sources into a single warehouse.
Data architects visualize and design the “blueprint” for the complete digital framework of an organization. Specialists in this domain often work with business leaders and data science teams to create new solutions for how information within an enterprise will be organized and used by various stakeholders. Data architects normally start off as data engineers, and move up in position as they develop expertise in information management.
Let’s return to the analogy of a data science team being a relay race. During the final leg of the race, a data scientist hands off the baton to a machine learning engineer. Data scientists develop theoretical models, which machine learning engineers feed into self-running software to make the model work on a larger scale. Compared to general data scientists, machine learning engineers have a strong focus in software engineering principles.
Business intelligence analysts work hand-in-hand with data scientists to analyze data and develop insights that can help improve business performance. Through the use of data visualization, data analytics, and data modeling, business intelligence analysts identify patterns and trends that help inform a company’s future strategy. Data scientists primarily focus on designing new algorithms to answer hypothetical questions, whereas business intelligence analysts apply existing algorithms to uncover information about the performance of a business.
Data visualization specialists present data with interactive visual tools, such as graphs, charts, and infographics. Visual tools allow data science teams to better comprehend trends, outliers, and patterns in data so that they can derive meaningful insights from the data. Visual tools can also be used to communicate information to business stakeholders in an impactful way.
Operations analysts identify areas of improvement in business operations using data provided by other members of the data science team. Then, they use statistical software to evaluate practical solutions to business problems and advise the managers on the best course of action. The operations analyst specialization requires complex problem-solving skills, but it’s less technical than other domains of data science.
This article aims to equip educational stakeholders with the knowledge that data can transform educational outcomes. It highlights the importance...
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