List of the Top Big Data Analytics Service Providers Companies in Kenya

The conception of big data has been around for many times, and utmost enterprises now realize that if they capture all of the data that flows into their operations, they can use analytics to prize tremendous value. Whereas a corporation would have gathered data, ran analytics, and unearthed knowledge for future decisions a few years ago, today’s organization can identify insights for current decisions. 

The new advantages of big data analytics, on the other hand, are speed and effectiveness. Working faster and remaining nimble gives businesses a competitive advantage they didn’t have before. Every day, massive amounts of data are collected that a standard computer tool can’t handle. These massive quantities of data are appertained to as” big data.”

Because standard computing approaches are unable to process such large amounts of data, a variety of solutions are being used. Huge data analytics is the process of extracting relevant insights from such raw big data. In recent years, the techniques used for big data analytics have become more popular.

Today’s businesses rely significantly on big data to acquire a deeper understanding of their clients. Big data analytics has a variety of uses in various industries. It has allowed firms to get to know their customers better than they know themselves, demonstrating the technique’s value.

Importance of Big Data Analytics

• Businesses can evaluate information instantaneously and make decisions based on what they’ve learned thanks to the speed of analytics mixed with the ability to study new sources of data.
• Cost-cutting. When it comes to storing vast amounts of data, big data technologies in analytics offer significant cost savings, as well as the ability to uncover more effective ways of doing business.
• New items and services are available. With the capacity to use analytics to measure customer conditions and satisfaction comes the implicit to give guests exactly what they want. More businesses are using big data analytics to develop new goods to fulfill the needs of their customers.
• Big data analytics assists businesses in employing their data and relating new openings. As a result, smarter business opinions, further effective operations, advanced gains, and happier consumers are the result.
• Big Data Analytics also aids firms in deciding on manufacturing and nodding for a product’s market entry. Big data includes customer input on a product. Businesses use this information to evaluate the performance of their product and, as a result, decide whether they should be continued or discontinued.
• The decision-making process has been aided by Big Data Analytics. Companies no longer need to wait days or months for a response.
• The world has become faster, and the decision-making process has sped up as well. Reduced response times have resulted in enhanced efficiency. Businesses no longer have to suffer significant losses if their product or service is not well received by clients because they can use the strategy to remodel their business model.
• When companies can monitor the client’s behavior on a regular basis, they may improve the customer experience on a personal level. Diagnostic analytics can be utilized to uncover solutions to the customer’s concerns. This will lead to a more tailored experience, which will ultimately lead to a better consumer experience.
• Big data analytics assists businesses in employing their data and relating new openings. As a result, smarter business opinions, further effective operations, advanced gains, and happier consumers are the result.
• Companies use big data to provide supplier networks, also known as B2B communities, with a higher level of precision. Suppliers can use Big Data analytics to get around the limits they face. It enables suppliers to use higher levels of contextual intelligence, which improves their chances of success.
• Platforms can use big data to deliver customized particulars to their target request. Rather than squandering money on ineffective marketing strategies, Businesses can use big data to conduct sophisticated analyses of customer trends. This includes evaluating online purchases as well as transactions at the point of sale. These data allow businesses to create profitable, specialized, and targeted marketing, allowing them to meet client expectations and increase brand loyalty.

Big Data Analytics Companies in Kenya

1. JanesonX Studio
2. Data Science LTD
3. Predictive Analytics Lab
4. Nakala Analytics Ltd
5. Bridge Analytics, Nairobi
6. Oracle Kenya
7. IBM Research Africa

Types of Big Data Analytics

• Descriptive Analytics

Descriptive analytics is a type of analytics that reduces and summarizes data into a readable format. It is thought to be a beneficial strategy for finding patterns within a certain client segment. Descriptive analytics can also provide insights into what has happened in the past, as well as tendencies to investigate further.

• Prescriptive Analytics

Businesses can use prescriptive analytics to figure out the best solution to an issue. It adds the benefit of managing a future occurrence, such as mitigating future risk, when combined with predictive analytics. The prescriptive analysis considers a variety of options and makes recommendations based on the results of descriptive and predictive analytics on a particular dataset. In the healthcare industry, predictive analytics is quite useful. It can be used to improve the medication development process, find the proper patients for clinical trials, and so on.

• Diagnostics Analytics

Diagnostics Analytics helps to provide a deep and in-depth understanding of a problem’s core cause. Diagnostic analytics can also help you figure out why your most loyal customers are churning and what they’re doing with their money. For the cause behind a given circumstance, data scientists resort to analytics. Diagnostic analytics techniques include drill-down, data mining, and data recovery, as well as churn reason analysis and customer health score analysis.

• Predictive Analytics

Predictive analytics uses past and present data to forecast future events. Market trends, consumer trends, and other market-related occurrences are examples of future incidents. Predictive analytics isn’t meant to foretell what will happen in the future. Because all predictive analytics are probabilistic in nature, they can only foresee what might happen in the future. 

Do you want to make sense of your data and make sound decisions? Well, contact us today!