Data Analytics Services & Solutions To Enabled Data-driven Growth
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Data Analytics and Visualization


65% of businesses around the world run data analytics tools to improve their business strategies

If your business doesn’t rely on data to solve problems, build revenue or track capital, then you will lose a lot.

What is Data Analytics & Visualization?

Data analytics is the science of analyzing raw data in order 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 analytics techniques can reveal trends and metrics that would otherwise be lost in the mass of information.
This information can then be used to optimize processes to increase the overall efficiency of a business or system.


Why do I need Data Analytics & Visualization?

Data analytics is important because it helps businesses optimize their performances. Implementing it into the business model means companies can help reduce costs by identifying more efficient ways of doing business and by storing large amounts of data.

Your company can also use data analytics to make better business decisions and help analyze customer trends and satisfaction, which can lead to new—and better—products and services. 

Close to 82% of businesses rely on data visualization graphics to portray business related metrics

Whether quarterly or yearly sales reports, employee appraisal analysis, leave tracker or product roadmap improvement. Data analytics and it’s visualization tools can make a huge difference.

“7x – the number of times our data analytics tool helped scale new businesses faster”

(FAQs) on Data Analytics & Visualization

Data Analytics and Visualization is the science of tracking, pinpointing, scrutinizing and implementing data-based strategies. These frequently asked questions are made up of queries that we get asked often.

You might have heard of Data Analytics & Visualization. But do you know what it means?
Data analytics enables making conclusions while analyzing data from informational resources. Data analytics uses strategies via technological processes and algorithms that manipulate data for human utilization and understanding. Data analytics helps businesses optimize their capacities.
You understand what Data Analytics & Visualization is, but can it help you?

Businesses are using analytics to make more informed decisions and to plan ahead. It helps businesses to uncover opportunities which are visible only through an analytical lens. Analytics helps companies to decipher trends, patterns and relationships within data to explain, predict and react to a market phenomenon. It helps answer the following questions:


What is happening and what will happen?

Why is it happening?

What is the best strategy to address it?

Collecting large amounts of data about multiple business functions from internal and external sources is simple and easy using today’s advanced technologies.

The real challenge begins, when companies struggle to infer useful insights from this data to plan for the future. Using analytics businesses can improve their processes, increase profitability, reduce operating expenses and sustain the competitive edge for the longer run.

What is the difference between Data Analytics and Data Analysis?

The difference between analytics and analysis is scalability.

Data analytics is a generalized term and is the umbrella over data analysis. Data analysis is the examination of data.
Data analysis includes data collection, organization, storage, and strategies and tools used for analysis.

Is it a good idea to hire an agency to perform Data Analytics?

Yes, it is. Building analytics function requires long term commitment and extensive resources. An organization has an option to seek analytical help from in-house resources or from outside analytical vendors or use both in parallel.

Any organization needs to spend considerable time and money to recruit and train in-house analytical help. At times they may not possess the required know-how to recruit such specialized staff or decide on the technologies that would be best suitable for carrying out analysis.

Agencies work with the management team to help the organization to adopt analytics. The organization has to trust and co-operate with the agency while sharing their data and researching it to make the analytics engagement a success.
How much time and resources are required?
The resources and time required for a data analytics project is dependent on a number of factors. The major factors being the scope and scale of the project, readiness and availability of required data, understanding of the analysis tools, skills and knowledge of the analytical team and most importantly, acceptance and approval from the management team to carry on the analytics project.

An agency such as Kilowott, defines a project timeline dependent on the factors listed above. Intermediary findings and analysis difficulties might alter the goals and objectives of the project. This might require the team to re-work the time and resources required for completing the project.
How much money does Data Analytics outsourcing cost?

For data analytical needs, an organization can decide to use data analysis softwares like SAS and SPSS, or seek help from custom consulting companies such as Kilowott to build data analytic capabilities. Today companies are even using a combination of the above.

The cost for outsourcing will depend on numerous factors that are best answered by contacting Kilowott.

Data Analytics & Visualization

Know Your Data Analytics & Visualization - A Quick Guide

Data Analytics and Visualization is a business science that analyses raw data to finalize conclusions.

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.

Prescriptive analytics

This technique suggests a course of action. If the likelihood of a hot summer is measured then the subsequent course of action needs to be adopted to sell more air conditioners.


Predictive analytics

This technique seeks answers to what is likely going to happen in the near term. What happened to sales the last time we had a shortage of personnel? How did festivals last year impact sales?

Diagnostic analytics

This technique focuses more on why something happened. This involves more diverse data inputs and a bit of hypothesizing. Did the weather affect logistics? Did that latest marketing campaign impact branding?


Descriptive analytics

This technique describes what has happened over a given period of time. Have the number of website traffic gone up? Are sales figures stronger this month than last?

Operational efficiencies

Data analytics enable operational efficiencies that provide the flexibility to support changing business requirements and priorities, improving your responsiveness, agility and speed to value.

Products and Services

Data analytics differentiate your organization by leveraging data and AI to extend into new domains, reinvent your offerings and evolve with the confidence you can scale to meet changing demand and priorities

Sustainable business

Data analytics can help visualize the skills needed for the future, and focus on building a sustainable workforce that is ready for what’s next.

Value realization

We help businesses define the vision and measure value potential, aligning on business priorities and developing a data strategy that can be articulated across the organization.

Data platform

We build a cross-functional data platform on cloud that connects the enterprise through a secure, single source of truth. Users across the business can access, explore and use insights in the context of their individual business needs.

Data Analytics & Visualization

Why Kilowott Data Analytics Services?

A data analytics company, Kilowott helps businesses from multiple industries integrate, aggregate, and analyze various data types from multiple data sources to address their most deliberate needs at department and enterprise levels.

Data integration and data warehousing

Extract, transform, load (ETL) or extract, load, transform (ELT) design and implementation; Data governance (data security, quality, availability, etc.) implementation, Data warehouse, data marts design and implementation.

Big data

Big data infrastructure setup and support, Big data quality and security management, Big data capture, analysis and reporting, Interactive dashboarding, Custom and pre-built visuals, Multiple visualization techniques (symbol maps, line charts, bar charts, pie charts, etc.)

Data science

Data preparation and management, Development and tuning of machine learning (ML) (including deep learning) models., Development and tuning of data mining models, Designing and implanting artificial intelligence (AI) solutions, Image analysis software development.

Data management services

Kilowott implements a robust data management framework to organize your processes of data collection, storage, access, security, analysis, etc. Business intelligence and data analytics infrastructure design and implementation, Ad hoc and scheduled analytics querying and reporting, and Natural language user interface.

Data analytics modernization

Kilowott helps upgrade the existing data analytics solution to achieve maximum ROI and meet the new data analytics needs.

Data analytics implementation

Kilowott designs and implements an analytics solution with the basic functionality to address your current data analytics needs and scale up as they grow. Your data analytics solution may include such elements as DWH, OLAP cubes, data visualization, data science, big data components etc.

Analytics as a Service (AaaS)

We carry out data analysis on a fully customized cloud analytics platform built and maintained by Kilowott.

Data analytics consulting

Kilowott’s experts help you choose an optimal data analytics strategy and guide you on designing, developing, implementing and improving a proprietary data analytics solution.

Managed data analysis

Kilowott’s data analysts collect and process your data to deliver quick one-time or recurrent analytics insights to you.


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