Building together data analytics tools for various fields

Jainya Tele Enterprises is a data analytics company that helps companies in over 30 industries combine, gather, and analyse different types of data from many sources so they can meet their most demanding departmental and enterprise-level needs.

By industry

Healthcare analytics

Monitoring and sending alerts based on a patient's health state.
Getting the best care for patients.
Risk assessment and personalised care plan suggestions for each patient.
Proactive care means noticing patterns and trends in a patient's health that need a doctor's attention.
Finding fraud in health insurance.
Medics can predict their task and make the best use of their work shifts.
Maximising the use of clinical area and tools.

Banking analytics

Monitoring of bank stability signs all the time.
Forecasts of how well an institution will do.
A full picture of your business.
Find chances for cross-selling and upselling.
Tips on how to handle customer service.
Modelling what might happen in order to reduce market, financial, and operational risks as soon as possible.
Checking for fraud.
Automatic checks for compliance and alerts for non-compliance.

Insurance analytics

insurance suggestions based on AI that are specific to certain groups of customers.
Finance analytics that include tracking the success of underwriting and making product-specific models of what could happen.
Monitor risks related to insurance by doing stress tests.
Operational analytics can help you improve customer service, claims handling, and other internal tasks.
Workforce analytics for judging agents' success, making changes to sales incentive programs, and keeping the best employees.
Information about how well outside organisations and partners are doing.
Analytics that can predict and prescribe for planning and improving insurance.

Lending Analytics

Giving information about borrowers' trustworthiness and figuring out the risks of default and non-performing loans-NPL.
Performance analytics for lending goods.
Suggestions for optimising a loan portfolio based on AI.
Find problems in the processes of underwriting, loan approval, service, debt collection, and other business activities.
Continuous tracking of compliance and alerts for non-compliance.

Investment Analytics

Benchmarking for each asset in a portfolio performance analysis.
Performance attribution, risk attribution, and factor exposure research.
Continuously keeping an eye on risks related to the market, credit, and cash.
Possible outcomes based on different levels of risk and stock rebalancing choices.
Figure out frauds like insider trading, pump and dump scams, HFT manipulation, and more.
Thoughts on how to handle taxes.
Monitoring and reporting for compliance all the time.

Manufacturing analytics

Overall study and improvement of how well the equipment works.
Improving the standard of the manufacturing process.
Planned upkeep for equipment.
Predicting and optimising power usage.
Root cause study for production loss.

Analysis of Retail Analytics

Analysing the success of a retail business and keeping an eye on sales and profits.
Looking at and predicting demand.
Multiple levels of product optimisation.
Plan and improve the assortment and display of goods.
advice based on data on the best ways to promote a product.

Transportation and Logistics Analytics

Planning and optimising operational capacity based on a study of incoming shipments, customer delivery schedules, available vehicles, and staff shift schedules.
The use of predictive analytics in car maintenance to find problems before they happen and suggest ways to fix them, among other things.
Predicting the market for vehicles.
Using an analysis of driving trends to figure out how much fuel the car should have.
for safe cargo transport using IoT data analytics (data on temperature, humidity, etc. of the cargo; data on driver behaviour; data on vehicle condition; etc.).

The Real Estate Analytics

By looking at market trends and property values, we can help you make smart investment choices.
Automated matching of buyers and sellers and personalised property suggestions for each customer.
Full portfolio management, including keeping track of spending and making predictions about cash flow.
Using rental, occupancy, and other property success KPIs to figure out and keep an eye on results.
Multiple ways to divide customers into groups, with AI-powered ideas on how to target each group.
Predictive analytics can be used to guess how much a property will be worth or to find homes that are likely to be bought or sold soon.

Professional Services Analytics

Multidimensional customer segmentation lets you automatically match customers with agents, make ads more effective, and give each customer a personalised experience.
Looking at how customers feel and how satisfied they are to make service better through data.
Operational data can help employees do their jobs better and make processes run more smoothly.
Use predictive analytics to guess what resources will be needed and how to best assign staff.
Using both internal and external data for financial analytics to find lost income and make a business more profitable.

Energy & utilities analytics

Monitoring of energy production and distribution all the time, with suggestions for improvement based on AI.
Looking at the role of green energy in the power grid.
Predictive and preventative analytics for upkeep.
By looking at trends of energy use, we can make better use of our resources.
Predictive intelligence to guess how much energy people will need.

Oil & gas analytics

Exploration management data to find the best places to drill and guess how much oil and gas is in the ground.
Use of predictive analytics to estimate the final recovery and forecast output rates.
Doing predictive and preventive repair on equipment.
Environmental effects: some ideas.
Real-time tracking of assets and processes, such as production, transportation, pipes, storage tanks, and pumping sections, with alerts sent right away.
Optimisation of the refinery and data for quality control.
Ideas about how to manage the supply line.

The Telecoms Analytics

Continuously monitoring and analysing network performance to find places with too much capacity and making the most of network capacity.
Giving information on how to handle customers to predict and stop customer turnover, make offerings more relevant, and keep more customers.
Identifying procedural bottlenecks and making optimisation suggestions based on AI.

Education analytics

Looking at what kids and parents say about the quality of the teachers and the classroom to make the service better.
an analysis of students' success with alerts about possible aid.
To improve teaching and learning, we need to know how people usually use learning tools.
Predicting enrolment to get the best use of resources.
You can use financial analytics to learn about things like grant income, endowment value, cash balance, pay, and more.
by looking at how well teachers are doing and giving advice on how to find and keep top talent.

Travel and hospitality

To get the most out of customer relationship management, keep track of and analyse interactions, preferences, and comments from customers.
Analysis of operational data, such as service quality and employee success.
Offering real-time, personalised suggestions on places to visit, places to stay, events, and other things.
Price optimisation using AI that takes into account market demand, customer tastes, and expected price changes.
Looking at how promotions, discounts, and loyalty schemes work and how they affect a business's ability to make money.
Calculating expected demand to get the most money from trips, hotel rooms, and other services related to this.

Analytics for media and entertainment

population segmentation on multiple dimensions with fine-grained comparisons, such as demographic breakdown vs. genre population.
Analytics for audience interaction that give you information about how customers behave and what they like across platforms.
personalised content suggestions in real time.
Analytics for content success.
predicting the desire for and popularity of content, including how well it will do at the box office.
Real-time targeting adjustments let you keep track of how well your advertising and marketing efforts are doing.
Keep an eye on how well legal standards are being followed, including those that deal with personal data.

Financial Analytics

Keeping an eye on a company's income, costs, and ability to make a profit.
Analysis of profitability and management of financial success.
Planning a budget and making long-term business plans.
Planning for and managing financial risk.

The supply chain analytics

Find the demand drivers, predict and plan for buyer demand.
Monitoring and judging the success of suppliers.
Predictive optimisation of routes.
Inventory planning and management include figuring out the best amount of stock to keep on hand to meet demand and avoid running out.
For better control of supply chain risks, finding patterns and trends throughout the chain is important.

Sales and Product Analytics

Analysing the sales route.
Using pricing data to come up with pricing plans.
Finding and guessing what sales trends will be.
Analysing the success of a product.
Keeping track of how customers use a product to find the problems that cause them to leave.
Comparing yourself to your competitors.

Customer Analytics

Predictive modelling and study of how customers act.
Customer segmentation helps make sales and marketing efforts more effective.
For longer customer lifetime value, make personalised cross-selling and upselling deals.
How to predict customer loss and deal with customer churn risk.
Analysis of how customers feel.

Asset Analytics

Monitoring and tracking of assets in real time.
Predictive and preventive repair, as well as making plans for maintaining assets.
Planning to put in assets.
Using analytics to plan and schedule how to update, repair, or get rid of assets?

HR analytics

Monitoring and analysing the work of employees and departments.
An study of the experience and happiness of workers.
Management and optimisation of an employee retention plan.
Analysis and improvement of the hiring plan for employees.

About Jainya Tele Enterprises

10 years working with data science and statistics.
For ten years, I've worked in business intelligence and data warehouse services. Five years with big data.
I've worked with Microsoft Power BI for seven years.
Knowledge of how to use machine learning, AI, data science, and picture analysis.
Internal project management office (PMO) to help with big, spread-out projects. Knowledge of how to use the Lean, Agile, and DevOps methods. Get PM certifications like PSM I, PMP, and more.
Make sure that the data analysis services are good and that the customers' info is safe.

The thing that makes Jainya Tele Enterprises unique

No matter what, we finish projects on time

The bad news is that a lot of companies on the market call project administration "project management."
Jainya Tele Enterprises does not do that. We do real project management, and no matter what,
we always make sure that our clients' projects are successful.

Why Jainya Tele Enterprises is a Good Analytics Partner for You

Automation that saves time

We set up self-service BI and automated data management and governance processes so that you can easily make reports on the fly without knowing how to code and so that your IT team doesn't have to handle data by hand.

Reports that are easy to read

We use different types of data visualisation to make the most important analytics insights stand out in each report and be easy to read quickly.

Reliable ideas resulting from trustworthy data

We bring together all of your different data sources into a DWH, which acts as a single source of truth for analytics across the whole company. Our strong ETL processes will make sure that your data is always correct, consistent, and full so that you can use it for reliable analytics.

Value-based data analysis

As a professional analytics consulting firm, we don't just make reports; our goal is to help you get the most out of your analytics solution and find new ways to improve productivity and cut costs that are hidden in your data.

How We Make Sure Our Projects Go Easily

With more than 30 years of experience in analytics services and well-known project management methods, we can keep projects on track even when time and money constraints arise or needs change.

To get good teamwork, we encourage unity, trust, and respect.

We promise that the information we get from you and store it safely.

We look at the project's risks ahead of time so that our estimates of time and money are accurate.

To help the software grow in the future, we keep and update true project documentation.

With the help of custom KPIs, tailored reporting processes, and effective task-tracking tools, we make sure that everyone can see how the project is progressing.

We speak your language and understand the unique challenges and needs of your field because we've worked in more than 30 different businesses.

For high user adoption and easy knowledge sharing, we're ready to train your team as users.

How much Jainya Tele Enterprises charges for data analytics services

Jainya Tele Enterprises offers a range of service choices to meet all of your data analytics needs. The price of data analytics services can range from $7,000 to more than $1,000,000, based on the type of service and how complicated the analytics needs are. Data quality and complexity, the type of processing (batch or real-time), the infrastructure and data sources that are already in place, the need for big data and machine learning/artificial intelligence (ML/AI) technologies, and other things all play a role in the costs.

As a Service Analytics

Jainya Tele Enterprises builds and maintains a fully customised cloud analytics tool that you can use to analyse data for a reasonable monthly fee.

Costs: $10,000 to $30,000 a month or more

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Modernisation of data analytics

Jainya Tele Enterprises can help you improve your current data analytics solution so that you can get the most out of it and meet your new data analytics goals.

Costs: $20,000 to $200,000 or more

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Services for managing data

Jainya Tele Enterprises sets up a strong framework for managing data that helps you organise how you gather, store, access, protect, analyse, and more.

Costs: $30,000 to $1,000,000 or more

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Managed data analysis

The data analysts at Jainya Tele Enterprises will collect and handle your data to give you quick analytics insights one time or on a regular basis.

Prices: over $10,000 for a one-time service; $7,500 to $14,500 per month

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Consulting for Data Analytics

The consultants at Jainya Tele Enterprises can help you pick the best data analytics approach and design, build, implement, and make improvements to your own data analytics solution.

Prices range from $10,000 to $50,000 or more

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Implementation of DA Implementation of data analytics

We create and set up an analytics solution that meets your current data analytics needs and can be expanded as those needs change. DWH, OLAP cubes, data visualisation, data science, big data, and other things may be part of your data analytics strategy.

Costs: $30,000 to $1,000,000 or more

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Ready to Talk About Your Needs?

Fill out our short contact form and tell us quickly what you need information about. Next, we'll do these things:

Give your case to a specialised sales rep who will get in touch with you within one business day to talk more about it.
We'll need two to five business days to put together a plan that includes a customised solution, a list of the people who need to be on the team, and estimates of cost and time.
If you agree with our plan, we'll put together a team and start the project in one to two weeks.

From automation to advanced data analytics, Jainya Tele Enterprises has what you need

Data integration and data warehousing

ETL stands for "extract, transform, load," and ELT stands for "extract, load, transform."
Implementation of data control (data quality, availability, security, etc.).
Designing and setting up data warehouses and data marts.

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Big data

Setting up and maintaining a big data platform.
Managing the quality and safety of big data.
Getting, analysing, and reporting on big data.

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Data science

Setting up and managing data.
The creation and improvement of machine learning (ML) models, such as deep learning models.
Making data mining models and fine-tuning them.
Coming up with and implementing AI ideas.
Making tools for image analysis.

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Business intelligence

The creation and implementation of infrastructure for business intelligence and data analytics.
Analytics querying and reporting on the fly and on a plan.
User interface that uses natural words.

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Artificial intelligence

Collecting and cleaning data to train ML models.
ML modeling.
Working on software tools that will use the results of machine learning.

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Data visualization

Dashboards that you can change.
Both custom and ready-made images.
Several ways to show information (symbol maps, line charts, bar charts, pie charts, etc.)

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The Latest Data Analytics Insights

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Jainya Tele Enterprises talks about how to build a data warehouse (DWH) efficiently, including methods, a plan, the skills needed, the software we suggest, and how much it costs to build a DWH.

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There are five best data warehouse software tools

Get an organised look at data warehouse software, including the most important parts of a DWH system and a list of our tried-and-true tools for building a DWH.

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The cloud data warehouse experts at Jainya Tele Enterprises give you a list of 6 cloud-based data warehouse platforms that cover 99.9% of all data warehouse use cases.

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How to apply business intelligence: the plan, the software, the costs, and the skills needed

Jainya Tele Enterprises can help your company set up business intelligence (BI) by giving you advice on the best way to do it, the tools you should use, how much it will cost, and the skills you need to make it work.

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An design, use cases, and key technologies guide for a real-time data warehouse

Scientists at Jainya Tele Enterprises talk about the structure of a real-time data warehouse, highlight its main parts and applications, and provide a list of the most trustworthy techs.

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