31 May How Big Data and Analytics are Changing the Caribbean Business World
Data analytics is the future of business. What does this mean? It means that businesses are no longer relying on intuition and gut feelings to make decisions, but instead they are looking at real time data to understand how customers behave and what their long term needs may be. This article will discuss how big data and business intelligence changed the business world and why we need to move along with it.
What is Data Analytics?
Data analysis has become a very popular and powerful tool for businesses. It is essentially the process of gathering data, analyzing it and then taking action based on what you’ve found out about your customers. The more information that’s available to a company or businesses, the better decisions they can make; this applies to all aspects of business services including marketing strategies, sales efforts and customer service. Along the way, as companies get to collect larger amounts of value based detailed data, businesses are realizing how much value there is in being able to see big data, so as to understand their customers needs better than ever before. Operating in this way allows them be more responsive and decisions based which leads directly into satisfying their needs even better than before!
The rise of Predictive Analytics
Predictive analytics is a part of advanced analytics that’s used to predict future events.
One of the most powerful big data tools in a company’s predictive arsenal is data analytics. It may utilize many different techniques, such as data mining, statistics modeling, and customer based analysis.
For example, predictive analytics may help analyze customer buying habits, which can assist marketing. Companies may use customer related data such as purchase location and frequency of purchases in a fluid way in order to determine where customers are going and what services they may want next or need most urgently. This is a big data tool for businesses looking for new ways to stimulate sales growth and increase marketing value.
Companies that have successfully integrated data analysis into their business processes have reported increased profits by an average of 28%.
Is Data Analysis in business intelligence that serious for sustainable development?
Yes it is! It’s not only serious, it’s mandatory.
In the last ten years, business analytics has grown from a straightforward description of predictive and statistical tools to an umbrella term covering a dynamic spectrum of business intelligence and analytics. Various terms such as data analysis, data visualization, advanced analytics, machine learning, regression analysis, and data quality have bombarded the business world, especially marketing.
The future of business analytics is big data as well as statistics, used to develop markets, boost marketing, evaluate customer experience and optimize revenue streams.
For too long data analysis has been relegated to the realm of IT. There was a time when most executives in any business did not know what an analyst could do for them, let alone how they were able to make their lives easier by providing important and helpful insights into business performance. But now, much is changing as big businesses are starting to see the value of data analysis and a set of data which can help their social media.
With the rise of big data tools, society has revolutionized marketing and business intelligence. These actionable insights are made possible by complex data. Businesses that are changing and invest in big data will be better poised to reap the benefits of data analysis and increase the value of their business.
Which sectors are adopting Data Analytics and depending on Data Science to boost business intelligence?
The answer is simple, all of them! Big Data Business Analytics has revolutionized every industry in every way possible, such as:
Big data has been incorporated into the education sector to help improve the overall experience of students. Institutions have been able to use data to better understand and address the needs of their students while also identifying trends and patterns that can be used to increase academic success. This may change education from being solely based on input and output statistics (i.e., grades) by having students learn what they need when they need it, instead of cramming everything together at the end of each semester. A recent study showed that when a student is given personalized feedback, they are more likely to improve academically. Remember, education is a business as well, the children are our customers.
Data has been a major factor for the transportation business as well, improving everything from fuel efficiency and routing precision, to identifying driver fatigue or distracted driving incidents in order to reduce accidents. In addition, this technology is being put into use by the construction industry with smart sensors on building sites capturing data about materials used and how long it takes them to install. This set of data is then fed back to project managers so they know when deadlines are missed or if projects need more resources allocated and where these should go based on an information collected.
Increasingly, companies are adopting data science for innovation purposes. With a wealth of raw data at hand, they can innovate by identifying influential factors that will drive future success metrics in order to maximize profitability or improve product quality within certain market segments. It is important for these companies to be able to capitalize on this opportunity as competition intensifies. For instance, with its new line-up of smartphones released recently (including iPhone SE), Apple has adopted machine learning algorithms developed through AI research division into all aspects of production including supply chain planning and procurement activities which resulted in more efficient manufacturing processes overall!
Data analysis deduced from big data was used to help conduct research on soccer teams, which helped identify their weaknesses and strengths in order to develop a winning strategy. By extension, this can also help sporting coaches better guide their athletes through the game.
In a 2016 study, Dutch soccer coaching organization KNVB experimented with big data to get real-time feedback about their players and regulate training sessions more effectively. They were able to use live tracking of athletes’ performances in matches via GPS devices and other sensors, aggregated by player position on the field, in order to measure how much effort they put into every movement while playing; this had previously been done manually through video footage analysis which was both time consuming and not always reliable due to subjective views from coaches or spectators.
Many governments have depended on data analysis for years, now the want for big data in business intelligence is just amplified. The UK, for instance, is even adopting big data tools to monitor and predict the spread of epidemics such as Zika. Furthermore, governments need hard statistical data in order to help shape policy that is sound and will actually have a positive impact the intended audience.
Big data can even improve disaster relief efforts by helping organizations identify the most vulnerable populations, helping organizations understand how to best allocate resources, tracking and predicting natural disasters, creating a more efficient disaster relief system and helping non-profit organizations understand what is needed in order for them to serve their communities.
Since data analysis is now being used to predict major global epidemics, the need for it in government will only increase. Data can be used to measure effectiveness of policy and then change policies accordingly so that they are more effective at achieving their desired outcome. For example, a country may want to decrease illiteracy rates among children between age five and twelve by one percent every year until 2020; using evaluating big data on this goal would allow them not just set specific goals but also track progress which would make sure the program was actually working towards its intended goal.
Analytics is helping insurers and companies evaluate customer behavior and optimize revenue streams as well as providing insights about disease prevention strategies that are employed by doctors and nurses alike. It’s also making it possible for hospitals to adopt and use individualized treatments based on the customers patterns observed from big healthcare databases spanning millions of patients all over the world.
Big data can be used in the customer service sector for a business like Uber or Airbnb that rely on reviews from customers as part of their decision making process when hiring drivers or vetting new hosts.
By adopting big data analytic techniques such as clustering analysis these types of businesses can identify big patterns among different groups of people who will provide them with valuable insight into what will most please each group while avoiding potential problems before they occur. This type of information would not only help fulfill current demand for companies but it could also predict future demand for services.
Analyst Insight on using big data
It is no longer a question of whether big data will change the business world, but instead, we are now entering an era where companies can’t afford not to employ big data technologies in their decision making strategy. With so much information available coming from all sorts of sources, it’s important that big businesses invest in predictive analysis with large volumes of data which could provide them with valuable insight into what might happen next on many levels.
The first step towards employing these methods should be understanding your own company’s goals and objectives before building out any type of big data technology solution. This way you don’t become overwhelmed by the vast amount of options or waste time trying to figure out the right cost or changing objectives while others get moving and find success.
Artificial intelligence in business intelligence is growing as our data intensifies
What is Artificial Intelligence (AI)?
It is an emerging technology that is changing the way people work, and transforming industries. Artificial intelligence processes data using machine learning algorithms to find patterns in large sets of unstructured information (big data).
The goal AI is to transform big data into insights about real-world problems. An example: an algorithm could be used by a medical researcher who wants to discover drug treatments for heart disease; it can analyze different types of research papers on cardiovascular health and suggest articles based on these findings which might otherwise go unnoticed.
Artificial Intelligence provides us with many opportunities including: better customer service, more accurate forecasting, improved national security, increased productivity and faster innovation in business, among others.
There are also risks which may be associated with this new tech as well such as increased surveillance and loss of privacy.
As this demand grows…
The future is now as big data and AI technologies develop exponentially to meet this demand. With predictive insights such as these, big companies can anticipate changes in their markets and create strategies accordingly with more confidence than ever before.
This technology empowers business intelligence analysts by providing them with deep analysis that would be difficult or impossible without access to vast amounts of big data which show patterns emerging from past behavior which could not have been predicted through simple linear extrapolation methods alone (such as trend lines). These advanced analyses are making it possible for big businesses to use these tools and identify trends earlier on, adjust course before they become a problem and maximize.
Data mining is a technique that extracts insights about the data from a large volume of raw and unstructured information.
It is an exploratory search for patterns in sets of structured or semi-structured data by adopting different techniques, some novel, others borrowed from statistics, machine learning or database systems.
When relevant big data techniques are put to use to provide statistical analysis, the process may generate new hypotheses as well. This can be done using data from a wide range of sources, such as social media or customer experiences.
Data Mining makes it possible for businesses to identify trends sooner on and adjust course before it may become a big problem. Data mining also maximizes the data that is collected so that more information can be gathered from less of an input, in order to help reach as many conclusions about the business’ strategy, even make the right decisions when possible.
In this sense, data mining enhances any decision-making process by adding valuable insights into how customers think and respond to products or marketing campaigns.
Once a pattern is found, it may suggest the type of additional analysis necessary, or provide an early indication that there is something going on and needs investigation. These suggestions are golden, as they can save a lot of time and effort by narrowing down the path to explore.
Big Data driven transformation is not a new trend. In fact, this information may been around since the beginning of civilization as we know it; but until now, digital transformation might have seemed like an impossible dream and an unattainable goal to many in our region, with few big data-driven projects underway or completed.
In the Caribbean, Antigua & Barbuda is an excellent example of forward thinking data interaction in the region, as they are set to become the first Caribbean future island nation. The government has put forward an initiative to digitize data, then using the data to make sense of policy. The data may then be used efficiently to see patterns and trends, or where they may be falling short. This will ideally help the country run much more efficiently.
Antigua & Barbuda has taken an initiative to invest in big data analytics and data visualization in order to understand their own policy needs better than ever before. They have understood the benefits of treating their people like the customer and marketing big data on a wide scale. This may be revolutionary!
Digicel, the mobile phone network and home entertainment provider, has been working hard on developing partnerships with other organizations who are experts at data analysis so that they can offer better services to their customer while still maintaining a competitive edge over other providers in the region. Digicel is simply one example of how big data and customer centered analytics may be employed as an opportunity for economic growth throughout the Caribbean.
One common mistake people make when utilizing big data analytics is neglecting qualitative analysis or traditional market research techniques like surveys because they think there’s too much information available from digital sources such as social media. But it’s called big data for a reason, all data is important to understanding the perspective of your customers, because the customer is always right.
So what now?
The Caribbean is one of the most dynamic places in the world. Entrepreneurs are creating new opportunities, and governments must invest in digital transformation which involves heavy emphasis on big data analytics for the future. The focus on innovation and inclusion is shifting mindsets to create sustainable economies that will fuel growth for decades to come.
Placing an emphasis on the importance of big data analytics is just one indicator of a larger trend, but have no doubt, data analytics is going to be one of the most lucrative markets in the world. The continued use of advanced data techniques in business and technology will improve the demand for future business analysts.