The organizations are dealing with an upsurge in volume, variety, and velocity of data. Globally, the data volume is about to reach 175 zettabytes by 2025. With it rises the management, processing, and analytics intricacies for organizations.
With businesses getting customer-centric, business data analytics helps develop and implement customer targeted strategies based on their need and demand. Using data analytics, organizations adapt to the changing needs of their customers and survive the stiff competition.
DefineRight (DR) is a data analytics company, an expert in big data and business analytics. We are serving the business operations challenges of organizations with a holistic approach, including data extraction, analysis, forecasting, and continuous reporting. Data insight guides make critical business decisions concerning strategy, product launch, innovation, investment, hitting new market segments, and several others ahead of competitors.
Industrial Challenges Ahead in the Context of Data
The Big data inflow, moving organizations to count on business intelligence and analytics for their strategic planning and actions. Business intelligence (BI) and analytics tools are evolving rapidly. They have shown a growth of 16% to 18% in the last five years, as reported by McKinsey. Therefore, organizations require to accustom to changing scenarios to remain competitive.
Listed below are some industry challenges related to data collection, modeling, analysis, and reporting.
Dependency on Advanced Data Networks
Advanced or vast data networks such as websites, applications, and CRM platforms, are the source of a large amount of consumer data, quintessential for organizations. Anticipating these data with the existing customer data, organizations can analyze the gaps to give a more personalized service to their clients.
Data Management
Managing sourced data and ensuring its accuracy, relevancy, and consistency is another complicated task for organizations. Since data-based solutions are crucial and fuel an organization’s strategic planning and growth, the accuracy and relevance of input data are of paramount importance.
The increase in new data sources, data security issues, and awareness of data privacy among customers is adding the challenge of data management.
Explore the Usage of Machine Learning
Harnessing the immense power of machine learning to create unique and new services that add value is complex. The application of ML can bring immense opportunism such as automation of customer service, data collection, data mining, etc.
Increase in Application of BI and Analytics Tools
Big data is pushing businesses to adopt BI and analytics tools at a large scale for data extraction and report generation. Analytical tools like Natural language processing, Information extraction, and retrieval increases efficiency, reduce the burden of understanding algorithms and the shortage of data scientists.
The Necessity of Interconnectivity
Interconnectivity of internal data sources, external data sources, BI & analytics tools, and IoT devices are crucial. It helps maintain the cohesiveness of data and build a consolidated data analytics machine for the business.
How Business Analytics Can Help
Business data analytics boosts businesses for a measure action approach instead of guessing, identifying gaps in products/services, need analysis, innovative solutions, potent marketing activities, and others.
Data analytics holds the potential to resolve several complex challenges of business. Some of the ways analytics transform business is as follows.
Data-driven Culture
Organizations infused with data-driven culture understand the value of data and its relevancy. The strategic moves at all levels of an organization get guided by data insights from a vast data network for optimum performance. It also aids in quick and precise data-driven decision-making.
Data-driven Culture
The application of embedded analytics tools delivers interactive data visualization, advanced analytics, and real-time reporting directly to enterprise business applications or user-interface applications. It makes embedded analytics more intuitive and eases the application of BI and analytics tools at a large scale.
Integration of analytical content with business process applications provides relevant information, making users work more efficiently.
Empowering with Data Literacy
Empowering the employees of an organization with data literacy fills the skills gap between data collection and data literacy. Employees gain the ability to read, analyze, work and communicate with data. It builds knowledge and enhances their ability to decision-making and communicate meaningfully to others.
A deep understanding of data supports better data management, solid data analysis, and digital transformation of a business.
Integrated Data and Analytics Strategy
An integrated data strategy is a plan designed to optimize how we acquire, store, manage, analyze, share, and use data. It acts as a road map for identifying your strength and weakness, reviewing and measuring your strategy, and offering the best possible solution. A holistic data and analytics strategy helps place organization strategy and addresses several challenges.
Significance of Data Science and Business Data Analysis Across Industries
Organizations infused with data-driven culture understand the value of data and its relevancy. The strategic moves at all levels of an organization get guided by data insights from a vast data network for optimum performance. It also aids in quick and precise data-driven decision-making.
Data science and business analytics combine data insight with mathematical operations to generate an automatic solution for existing problems. These technologies are revolutionizing various industries to change their primitive process and bring innovation, customer-centric approaches, solve existing problems, optimize their performance, etc.
Data Science combined with business analysis is transforming industries; some examples are as follows.
Data analytics Transforming Healthcare
The Healthcare industry is one of the great examples of data science applications and their impact. Medical professionals use data science to identify a new disease at its initial stage by reading the patients’ records and providing immediate help. Data analytics accelerates drug discovery & development, speed up clinical trials, personalized & targeted medications, drive marketing & sales campaign, etc.
Data Science in Automobile Industry
Automobile Industry is continuously coming up with innovations and applications like self-driving, autopilot flying, automatic transport, etc. These innovations and applications require the usage of data science to understand the unique advantage it will bring for the users and something new in the market. With data science, the automobile sector is opening new opportunities in terms of technology and innovation.
IT Leveraging Machine Learning
The IT industry is data-driven, and the application of data science and ML helps identify the impact of technological changes, like changes made to a website or an app, whether it will add a customer or lose the customer base. The industry is applying data science to identify network security-related issues and improve security measures.
Data Science Innovating Banking and Finance
Data science & analytics is helping banking and finance to detect frauds, risk modeling for investment banks, analyze credit risk, operation & liquidity risk, sales analysis, and others. Thus, the technology is supporting to establish a more stable system.
Predicting Nuclear and Power Demand
With the increasing demand for power, power and nuclear power industries need to find the effects of nuclear power sources, their impact on natural resources, etc. Data science helps find the safest potential and develop AI bots for handling enormous power sources.
DefineRight – A Solution for Complex Business Operational Challenges
DefineRight aims to support businesses in handling business operation challenges with its data insights through advanced data analytics tools, technology, and solutions. We indulge in an end-to-end data analytics solution, from data sourcing, management, analysis, and reporting.
As part of our business enablement services, DR enables the business to overcome their unexpected challenges, plan and implement a customer-focused strategy, identify product/service gaps, bring innovative solutions, boost marketing and sales, etc., to mention a few. We help organizations define their problem right towards the solution using business process automation, application engineering, change management, and several other services.