“He who owns the information, owns the world.” This statement by Nathan Rothschild takes on a new meaning in our digital era. Today, a company can extract valuable information from virtually any data about clients, competitors, and the market. Data analytics helps businesses grow faster by making strategic decisions based on the analysis of data across multiple dimensions. In this article, Andersen’s experts in Data Science consulting will share how Big Data analytics and Location Intelligence technologies are affecting businesses and what prospects are expected in this area.
The essence of Big Data
The amount of data in the world is growing along with technological advancement. Big Data means large volumes of structured and unstructured data coming from different sources at high speed. Big Data emerged in the mid-2000s and soon became one of the most popular technological trends.
To process Big Data, various tools are used depending on the task specifics of a project or company. Among them are such programs as Apache Hadoop and Cassandra for data storage, Xplenty, Apache Spark, and Talend Open Studio for data processing, and others. Each of the world’s cloud providers – AWS, Azure, GCP, and others – has its set of services for storing and processing an unlimited amount of data.
Dedicated tools help to store, process, and analyze Big Data for conducting survey data analysis based on it. To understand the work of such software, we can imagine the following: the tool uses Big Data as a construction material to build large-scale business processes. Based on the knowledge obtained, companies make the most important decisions for further development.
Big Data for businesses
Big Data technologies enable companies to collect and analyze data, build predictive models, conduct inverse testing, and simulate scenarios (What-If Analysis).
Big Data and Predictive Analytics. Data that are collected, processed, and analyzed timely allows for the prediction of possible courses of events. This is applicable to many business sectors, including the manufacturing industry. Big Data expertise enables companies, for example, to predict the likelihood of a production line failure and prevent the breakdown.
Big Data for cost reduction. Another area of Big Data application is production streamlining and product cost reduction. Big Data includes information about the entire production cycle. By analyzing this data, one can draw a conclusion about how to improve the product and reduce the cost of manufacturing even before its launch.
For example, Intel applies Big Data analysis for processor production. If the company neither collected nor analyzed data at every stage of product development, it would have to conduct myriads of testing cycles until the processor is fully ready for release. Working with Big Data helped the company save about $30 million on tests that weren’t needed.
Big Data for efficient marketing. Big Data is used to perform various marketing tasks such as segmentation, positioning, ROI measurement, and so on. Each company’s strategy is aimed at getting an insight into the market. Applying Big Data gives a business many benefits: a clear vision of its consumer, identification of free niches, knowledge of competitors’ strengths and weaknesses, online reputation management, the ability to predict trends, and, as a result, competitiveness.
Big Data and Location Intelligence. Another area where Big Data is actively used today is location-based analytics. This is a technology that takes geographic data as a basis and analyzes it to solve business challenges. It emerged on the basis of geoinformatics – a science that studies digital methods of processing geographic information. Data for the analysis is obtained from various sources – for example, from a satellite.
What Location Intelligence is used for
Today, Location Intelligence is applied in the following fields:
– communications and data transmission: network planning and design;
– financial services: branch location optimization, market analysis and decision-making on mergers or acquisitions, industry analysis, risk management;
– government and society: population census data updating, analysis of crime and criminogenic situation by the district at the request of law enforcement agencies, emergency response, redistricting, tax jurisdiction zone determination, urban planning;
– environmental protection: environmental indicator and climate change tracking, rational resource management;
– healthcare: medical market segmentation, search for growth directions, medical facility construction planning;
– education: student intake planning, help in choosing a school, campus and educational building design;
– agriculture: effective land use planning, yield analysis and distribution of land for planting various crops;
– hotels and restaurants: client profile analysis, target marketing, planning of expansion and locations for opening new outlets;
– insurance: client address verification, risk and claim management;
– marketing and media: ad targeting, demographic consumer evaluation, media and ad planning;
– real estate: demographic analysis, client data analysis, pricing, design;
– retail: site selection, ways to increase sales for each store, identification of ineffective stores, demand analysis, competitor supply analysis;
– transport: route monitoring and planning, efficient logistics.
Location Intelligence provides a means for optimizing the performance of many business lines by analyzing data and identifying patterns.
What high-quality Location Intelligence requires
Good visualization is essential for spatial analytics. That’s why Location Intelligence tools use 3D modeling and AR/VR technologies. For example, when planning the construction of an oil platform in a remote area, in the initial stages, the analytics from Location Intelligence is enough to understand where to place it. The combination of 3D and AR/VR technologies helps to accurately visualize these areas.
There are many other examples of how LI allows businesses to grow and change the world for the better. It should be noted that this area is of great interest to custom software development companies. LI is actively developing, applying all new methods and technologies.
Conclusion
What’s more important: analytics or intuition? Big Data allows businesses to combine both of them to make decisions. The key to McDonald’s success lies in the right combination of both methods. If the business owners had opted for only one, their fast food cafes would hardly have turned into the largest global chain. Applying LI allowed the company to draw conclusions about the right locations for new restaurants that were successful.
Big Data and Location Intelligence make it possible to discover new opportunities and create new types of businesses that combine data from different industries. Thus, reliable, relevant, and visual data provides useful information about products and the market, optimizes business processes, and brings significant economic benefits to companies.
