The advent of the New Year brings new possibilities, challenges and several other advancements with it. No matter which industry or niche one is working in, changes are fundamental to it and help it transform into something new. It is the changes that drive innovation and capture new ideas for research and development. And just like every other technology that is on the brink of transforming the world, big data and analytics are one of the biggest technologies causing a modern shift in business.
Big data and analytics are saviors in today’s world. They are helping businesses to leave their traditional processes behind and enter a more advanced and sophisticated world of analysis. Big data when combined with analytics open an altogether new area of possibilities for business. They can analyze their present business, competition in the market, client demands and criticism along with accelerating innovation trends.
Therefore, owing to the multitudinous benefits of big data development services and solutions , more and more organizations are embracing it with each passing day. It is also because businesses are moving into an era of data-backed decisions. Be it an objective or subjective goal they’re looking out for, data is the only element with all the answers.
While we are already excited about the existing bundle of features that data analytics and big data have for the world, businesses are inquisitive to know what lies ahead. Researchers and experts suggest that certain disruptions are already on the cards and ramping things up with more intricate and modern information than ever before. Let’s take a look at some of the most spectacular trends:
Whether we choose to believe it or not, businesses like tasks being automated. Not only does it helps them save costs and reduce the burden of manual labor, but also adds up to their efficiency. While this will bring a higher pace of productivity, it will also enable resident data scientists to perform more extensive use of data. Automation in data analysis will help businesses seek their goals in a much faster and efficient manner.
Researchers say that augmented analysis will be the next wave of disruption hitting the world by next year. It traditionally uses the latest technologies like AI and ML to alter the way analytics content is created, deployed and shared. Soon, augmented analysis will be the one driving areas such as business index, data science and ML platforms, embedded analytics, etc. Furthermore, as platform abilities develop, organizations will be more reluctant than ever to adopt augmented analysis.
The expansion of machine learning models and automated service level management will diminish data management tasks by 45 percent in the coming year. Merchants will now be seen including AI and ML capabilities to make self-arranging and self-tuning procedures inescapable. As a result, it will reduce the burden of manual undertaking in data management and enable skilled professionals to concentrate on more critical tasks.
Continuous Intelligence is a design pattern where real-time analytics are incorporated within a business activity; this enables businesses to prepare the present and historical information to endorse activities because of events. As we move into a year ahead, more and more business frameworks will fuse continuous artificial intelligence that utilizes real-time content data to support and enhance high-level decision making.
This year, the analytic queries are produced by the means of search, natural language processing or voice. These will also support analytics and deployment of business intelligence from 35 percent employees to over 50 percent.
Currently, most analytics tools expect the clients to pick up data components and place them on a page to raise any questions. With conversational analytics in the future, inquiring and posing questions will be as simple as a Google search.
Read More: Internet of Things Security Challenges
Artificial Intelligence models are progressively helping businesses make faster and better decision. However, they consist of unpredictable secret elements that give no idea of how the model arrived at a particular decision. But to gain the trust of users and partners, organizations must be able to explain the decisions made by AI. Thanks to explainable AI for data analyses that will auto produce a clarification of models as far as precision, traits, statistics, and features in modern language.
By the end of this year, the world will have close to 20 billion IoT devices. This will provide an abundance of data for analysis and organizations will be more reluctant than ever to use analytics solutions for IoT gadgets that provide information as well as transparency. However, the companies that face the lack of data scientists will be deprived of the advantages of IoT.
In the years to come, graph analytics consisting of graph processing and the database will reach its peak and fasten the planning of data. They will also empower progressively precise and adaptive data science. Furthermore, reduced cost alternatives like cloud and GPUs will make graph analytics possible for accelerated deployment.
With the cost of memory reducing as of late, in-memory computation will turn into a mainstream technological solution for a plethora of advantages in analytics. This is exceptionally profitable to companies because the large amounts of big data and analysis performed over it require much faster CPU performance, along with faster storage and larger amounts of memory.
With an increase in the data of consumer devices, businesses will utilize data analytics to predict consumer behaviors and make devices and applications more personalized to their use.
The next year will surely have a lot of exciting developments in the fields of big data and analytics. Now that you know what some of these will be, it is better to start preparing for these and embrace the waves of change.
Dairy Delivery Software
Native Milk always had to deal with route optimization to maximize profit and frequent changing of delivery boys. While this was easily manageable manually in offline business, it was a big headache when their business went digital.
We developed a mobile application for the drivers with route optimization. The total delivery area is divided into various routes and orders are sorted according to different routes. A driver is then assigned a single route.
PlanTech, (Construction Project Management software Case Study) a well-established US based construction company with huge projects, needed an improvement of their business processes and better optimization of their resources. As their business expanded, projects continuously got delayed which resulted in lawsuits by unhappy clients. We faced a variety of challenges to develop niche technological solutions for a company involved in the construction industry.
We designed separate web and mobile applications for foremen i.e. project managers and for construction staff (labourers). The applications has synchronized features such as calendar, attendance etc. that were updated real time Simple user interface for the layman was developed after many iterations and approval from the client.
We developed a dedicated central project management panel. The purpose was to have a centralised system update where all team leaders from different departments could update on their tasks at work.
We needed a fast technology to synchronize the source data to our system.
We had to run our programs real time during the horse race.
We ran our calculations on the given data, but by the time we generated an analysis of the probable winner, the market trends and positions of the race horses altered so our result had no value.
The reason behind using node.js is that we were able to establish a swift and persistent connection between betfair and our algorithm.
We could run our program with race data and generate results using the latest trends up-to-the-second with more than 99 % of the source data matching with our index.
On-Demand Delivery App
The client was clear with their needs but was not tech savvy enough to state specific requirements.
In GetIt the driver and vendor are treated as separate entities unlike a regular taxi application where such division does not exist.
We initiated brainstorming sessions with the client to plan out the project.
We built application functionality to optimize the process while simultaneously taking all stakeholders into account.
The client had an understanding of NFC but they had no idea of how the technology behind NFC works.
The client needed a secure platform as they wanted to keep the customer data secured.
We did a knowledge transfer with the client and explained the technology behind NFC and QR code.
We undertook a variety of security measures to prevent any leakage of user data.
The oldest insurance company of Lebanon reached out to us. They needed to digitize their operations and develop a lending application.
The target customers of the bank were mostly laymen with not much technical know-how. They consisted of old people, rural families, middle class urban families etc. Thus digitization was a challenge.
We developed a mechanism for the bank to directly disburse the loan amount to the customer’s bank account. This saved a trip to the bank of the customer and saved a lot of time for both the parties.