Why Data Analytics is important in the technology space?
Data is the oil of the 21st century, and analytics is the combustion engine.
In 2020, every person generated 1.7 megabytes in just a second. An immense amount of data is produced and stored every day. But it’s not enough just to collect and store big data—you also have to put it to use. With this data, we can improve efficiency in operations, improve customer experience, create leads over a specific customer, and get better marketing insights.
It happens through analysis done with the data which is collected. Analytics are used to make better decisions making in business, optimizing their performance.
Data & analytics are important because it allows businesses to make informed decisions based on data. It also helps businesses to track and analyze trends, which can be used to improve business operations. Additionally, data & analytics can help businesses to identify opportunities and optimize their marketing efforts.
Data analytics is the process of studying data sets in order to draw conclusions about them. This can be done through a variety of methods, including statistical analysis, data mining, and machine learning. Data analytics can be used to find trends and patterns, make predictions, and help make decisions.
Insights and Analytics
enabling important metrics and analytics, as well as discovery and business intelligence to enable company insights. The team consists of business analysts and professionals in Tableau, Spotfire, Power BI, Microstrategy, and other tools who analyse the organization’s information needs and develop best-in-class solutions.
Management of Data
the whole range of data engineering, data quality, extraction, transformation, and warehousing (ETL), as well as establishing data lakes and data warehouses, allowing businesses to use data for cutting-edge analytics and insights.
Data Science and AI/ML
ML models can be created by a team of data scientists and business analysts for applications ranging from text analytics to forecasting and predictive modelling. Aside from chatbots and conversational AI.
Solutions for gathering, storing and analyzing big data at the enterprise level.
- Data Analysis
- Data Architecture
- Data Integration
- Data cleaning
- Data Transformation
- Data Repository
- Disaster Recovery
Security Support & Maintenance
Data Reporting & Advanced Analytics
Transforming data into real insights and getting them into the hands of the people who can make an impact.
- Data Visualization
- KPI Definition
- Analytics Automation
- Reporting Solution
- Dashboard Solution
- Bi Portals
Advantages of Data & Analytics
- Helps organizations make better decisions by understanding data patterns and trends.
- It can optimize business processes by identifying inefficiencies and areas for improvement.
- Improve marketing and sales strategies by understanding customer behaviour and preferences.
- Helps detect fraudulent activities and improve security.
- Improve website design and user experience by understanding website visitor behaviour.
- Protect the privacy of individuals by ensuring that data is used responsibly and appropriately.
- Helps organizations save money by reducing operational costs and improving efficiency.
- Data can be used to improve marketing strategies and campaigns by identifying opportunities and optimizing marketing strategies.
- Can be used to improve customer segmentation & improve customer retention.
- Data can help identify cross-selling and upselling opportunities.
Our goal is to uncover new opportunities through decision-making, provide innovative ideas, making leads in marketing and sales through insights.
The key types of analytics are:
- Descriptive analytics tell us what happened.
- Diagnostic analytics tell us why something happened.
- Predictive analytics tell us what will likely happen in the future.
- Prescriptive analytics tell us how to act.
We can help you achieve this. Our team of experts at Indsafri will guide you all the way to make the best use of the data to bring valuable insights.