How Can Big Data Be A Catalyst For Business Growth?
No matter which part of the world or domain you’re running your business, organizations will allow gain valuable insights and data.
Big data always plays a vital role in all aspects and is beneficial in anticipation of requirements.
Data is the ideal fuel of business and anticipation of new requirements. The thing that separates Big data from others is not beyond the tech industry. Its advantages are prevalent in healthcare, education, governance, retail & manufacturing, supply chain management, etc.
Since companies are foreseeing this as a sure-shot formula, they expect the Big data to grow $103 billion by 2027. The software industry is leading the market with a share.
The big data and business analytics market touched $169 billion in 2018. And it is estimated to grow by $274 billion by 2022.
What is Big Data?
Big data comprises essential —-tools and processes usage and management of extensive data sets in an organization. With that concept, enterprises can understand patterns & preferences, database generation by interacting with people with varying systems.
Big data emerges as a new fundamental for many reputed companies. It is beneficial in tracking competitors and new entrants to obtain and innovate constantly since it is widespread in almost every sector running from banking to information technology.
The definition of big data in four Vs.
Google
Volume
The data-centric nature of organizations accumulates data from various business transactions, smart (IoT) devices, social media, and many more. In the past, storing data created many problems, but cheaper storage on platforms like data lakes and Hadoop has eased the burden.
Velocity
With the rise in the (Internet of Things), data streams into businesses grew at an unprecedented speed with urgency. RFID tags, sensors, and smart meters necessitate dealings with these torrents of data in near-real-time.
Variety
Data availability in all formats – from structured, numeric data in traditional databases to unstructured text documents, emails, audios, videos, stock ticker data, and financial transactions.
Veracity
The quality of data needs to be of optimal quality. Data Veracity ensures valuable analysis and contribution in a meaningful way.
Why Is Big Data Important?
The essence of big data is beyond volume and focuses on the feasibility of the data.
1) cost control, 2) time-saving, 3) new product development and optimized services, and 4) smart decision-making.
When you complement big data with high-powered analytics, you can accomplish business-related tasks such as:
- identifying root causes of failures, issues, and loopholes in near-real time
- Detecting fraudulent activities before it affects your organization.
- Recalculating high-risk portfolios in a fraction of minutes
- Producing coupons at the point of sale based on the customer’s buying pattern
“Big data is poised to reach USD 123.23 billion by 2025”.
Impact of Big data on Business
Using big data, companies focus on improving customer service and a spike in profit. Improved customer service is the primary goal of the business.
The other benefit is realized in target marketing, cost- reduction, and improve processes’ efficiency. It makes companies store large volumes of data, enabling significant cost benefits with enhanced security.
Technologies like Hadoop and analytics are a huge hit. Indeed, Big data has been phenomenal in the DECISION MAKING AND ANALYSIS OF INFORMATION.
Big data can extract social and economic benefits—one of the reasons why several governments are deriving plans, formulating policies for Big data development.
Adopting agile technologies is one of the reasons why big data analytics has evolved while increasing focus on advanced analytics.
AS OF NOW, NO SUCH TECHNOLOGY CAN SURPASS BIG DATA ANALYSIS. This is why companies work in tandem with technologies like AI, quantum computing, in-memory analytics, and predictive analytics. Such technology trends are likely to spur the demand for big data analytics in the forecast period.
The turnaround caused in large and small enterprises relies on Big data for business since it is the queen of data analytics.
Enterprises from all business verticals are exploring how they can use Big data in mainstream business. Big data can improve productivity, identify customer needs, and offer a competitive advantage with sustainable economic development.
What Are The Elements of Big Data Environment?
Big data and analytics comprise various components and functions. Such core aspects can factor into project plans upfront. The traditional data warehouse can take the step of Big data architectures to store structured data. The architecture features data lakes that hold different data sets in native format, typically built on technologies like Hadoop, Spark, NoSQL databases, and cloud object storage services.
A solid architecture creates Big data pipelines —–to funnel data into repositories and analytics applications.
Big data analytics
Big data systems are used for analytics applications, ranging from straightforward BI and reporting to advanced analytics by Data science teams. ML is one technology that has got the maximum advantage from the availability of big data. Now it is widely used by businesses to find anomalies in large data sets.
For more insight, you can read articles by Kathleen Walch– Principal analyst and Managing Partner at Cognilytica, explaining how the blend of big data and ML can make analytics more effective.
Big data collection
Big data is processed and analyzed to collect internal and external data sources. However, it can be very tricky as there is a large amount of data and many resources. Moreover, data security and privacy add to the challenges as businesses must comply with GDPR, CCPA, and other regulations.
Big data integration and preparation
Integrating data sets is one of the attributes of Big data environments—– new requirements and challenges, unlike traditional data integration processes. Big data is enriched in volume, variety, and velocity, nullifying the possibility of extract, transform and load procedures. Learning new integration techniques helps the data management team for Big data.
Analysis(data discovery, cleansing, and variation) followed by integration. In data lake, the stored data is available in raw form, the formation of data by data scientists or data engineers to suffice individual analytics applications.
Big data governance
Effective data governance ensures consistency of data collections in compliance with privacy regulations and internal data standards. However, governing Big data poses new challenges for managers because of the extensive data they often oversee. Data quality management is a crucial facet of Big data deployment since data quality requires new processes for fixing errors and quality issues.
Big data Technologies & Tools
Hadoop’s built-in MapReduce processing engine is partially eclipsed by Spark and new technologies, and Hadoop components are used by organizations. All such technologies are options for a big data environment, including :
Processing engines
Examples include Hadoop MapReduce, Spark, and stream processing platforms like Samza, Kafta Flink storm, and Spark’s structured streaming module.
Storage repositories
Examples include Hadoop Distributed File System and cloud object storage services like Amazon Simple Storage Service and Google Cloud Storage.
NoSQL databases
Couchbase, CouchDB, Cassandra, HBase, Cassandra, MarkLogic Data Hub, MongoDB, Redis, and Neo4j.
SQL query engines. Examples include Drill, Hive, Prest, and Trino.
Data lake and warehouse platform
Examples include Delta Lake, Google BigQuery, Amazon Redshift, Snowflake, and Kylin.
Commercial platforms and managed services
Examples include Azure HDInsight, Cloudera Data Platform, Amazon EMR, and Google Cloud Dataproc.
How Is Big Data Is Used in Businesses Across Industries?
Financial services, manufacturing, retail & telecom, are some leading industries harnessing the advantages of big data solutions. Business owners increase investment in Big data solutions for better optimization of operations and managing data traffic. Also, Vendors are adopting Big data solutions for better supply chain management.
Banking, Financial Services, and Insurance (BFSI)
The BFSI industry implements big data and analytics on a large scale to become more efficient, customer-centric, and more profitable. Likewise, financial institutions use big data analytics to eliminate overlapping, redundancy, and tools for easy data access.
Banks and retail traders harness big data for sentiment measurement and high-scale trading, among others. This sector also relies on big data for risk analytics and monitoring financial market activity.
Retail
The retail industry gathers many data through RFID, POS scanners, customer loyalty programs, etc. Using Big data, retail firms check fraud and do real-time analyses of inventories.
E-commerce
The importance of big data for an e-commerce business is commonly understood; the more you know, the more is the profit. Companies keep an eye on consumer behavior, purchasing history, and products for tracking.
The more you know about your customer, the more profits you generate from your e-store. Data on real-time checks of customer behavior, purchasing history, and products liked to allow tracking high-demand products and forecasting trends to introduce best-selling products. Pricing analysis, inventory management are things for technology to do.
Manufacturing
A big chunk of data goes unnoticed in manufacturing and plaguing the industry with several challenges like labor constraints, complex supply chains, and equipment breakdown. Big data ensures a new way to save cost and improve product quality.
Logistics, Media, and Entertainment
Big data helps online retailers manage inventory in line with challenges specific to one or another location in the logistics sector.
It helps analyze customer’s personal & behavior data to create detailed customer profiles.
Energy(Oil & Gas)
In the energy sector, big data facilitates better decision-making. Managers can make better decisions regarding oil reserves through an in-depth analysis of geometry. Agencies can also leverage Big data to ensure that all the safety measures are up to the mark. Global companies are churning the advantages of Big data. Big data adds analytics and other technologies for managing data efficiently.
Nonetheless, the usage of big data is negligible in several industries, such as healthcare, oil & gas, and so on, and goes a long way ahead. Since the technology is expensive to adopt, and companies still don’t take it as a reference.
Future Trends in Big Data
Organizations run Big data systems in the cloud using vendor-managed platforms as a service—– to simplify deployment and ongoing management.
As quoted by Cognilytica’s Schmelzer,” top significant data trends move towards cloud-enabled business with unlimited new data and pay for storage and compute capability on-demand without maintaining large and complex data centers.”
The following notable trends
- Increase data diversity, driven in particular by accumulating data volumes from IoT devices, leading more organizations to adopt edge computing to better handle processing workloads;
- Enhanced benefits of AI & ML technologies, both for data analytics and chatbots, to provide better customer support and personalized interactions
- Implement DevOps practices for managing data flow and focus on data stewardship to help organizations deal with data governance, security, and privacy issues.
Let’s Now look into Big data Benefits :
Re-Development Of Products
Big companies across the globe use Big data technology to give excellent value for customer feedback. It is beneficial in performing necessary changes and re-development of their products.
Big data is also very helpful in testing several variations of innovative computer-aided design in a few seconds. It helps you gather information about lead times, performance, cost, technology improves, and raises the business productivity of some manufacturing processes.
Evaluation of Risk and Data safety
If you’re not proactive on the business front, you are bound to fail!
Big Data results are beneficial in predictive analytics to scan and scrutinize newspapers reports and social media feeds. It helps organizations update on the recent development in the industry.
The technology is beneficial in mapping the entire data landscape throughout the company. You can study different types of internal threats and maintain critical business information. Data remains protected using appropriate ways as per regulatory methods.
Cost Optimization
Big data tools like Hadoop and Spark provide cost-beneficial aspects for storing, processing, & analyzing a large amount of data. These data tools help in efficient and cost-savvy ways of conducting business. Many industries present a great example of cost-reduction benefits.
You can always anticipate products most likely to be returned and allow companies to take suitable measures to reduce losses on returns.
The logistics industry demonstrates how big data is beneficial in cost reduction. Usually, ROI from products is 1.5 times greater than actual shipping charges. Big data analytics help companies to minimize product return costs by forecasting product returns. They estimate which products are most likely to be returned, thereby allowing them to take appropriate measures to reduce losses on returns.
Dialogue with Consumers
The availability of data & information is making customers more competent than before. People are likely to research and compare products on various media channels in the consumer-centric world before making up their minds for buying. Also, it is beneficial in the integration and physical shopping spheres. Business organizations always engage in one-on-one and real-time conversations with consumers.
Fosters Competitive Pricing
Big Data Analytics is beneficial in the real-time monitoring of competitors. It allows keeping track of past actions of competitors and adopting strategies. Big data analytics offers real-time insight, will enable you to —
- Assessment of price change impact
- Implement competitive positioning for maximizing company profits
- Evaluation of finances for a vivid business status
- Implement pricing strategies based on local customer demands, customer purchasing behavior, and competitive market patterns
- Automation of pricing helps businesses maintain price consistency and eliminate manual errors.
Control and Maintain Online Reputation
For businesses across the globe, the inclination towards the online domain has become a natural phenomenon. After all, monitoring, checking, and improving online reputation will hold the key.
Customers saying about various online social media platforms affect how potential customers will view your brand.
Using specific tools in the online sphere is very useful to understand products/services for the brand. Once you know customer grievances, you can only improve services to grow your online reputation.
Conclusion
Big Data gives much-needed penetration to competitive business advantages. It leverages business organizations in the private and public sectors in several ways. Business organizations use analytics, as well as identify target business customers. In this way, it plays an essential role in assisting businesses to create new services, products, and experiences with benefits like:
- New revenue opportunities
- More effective marketing
- Better customer service
- Improved operational efficiency
- Competitive advantages over rivals
