Develop new Products and Services
The era of big data has created substantial opportunities for software products such as BIRD in helping global organizations develop products aligned with consumer demands in some of the following ways:
- To inform and guide new product developments along with its numerous benefits. BIRD can help firms develop products that connect with the consumer in a much deeper way than ever before, provide increased consumer value, and minimize the risks associated with a new product’s launch.
- BIRD can help Marketing agencies learn and align their new campaigns and products using the information kept in the social networking sites like Facebook, Twitter and Instagram this would help meet user specific needs and improve such advertising mediums.
- Using the information in the social media such as the preferences and product perception of a target customer group to provide correct guidance and insight to product-based companies so that retail organizations can plan their production accordingly.
- Through BIRD insights and smart data discovery features, firms can also identify needs it might not otherwise have captured. For example, LinkedIn has used Big Data and data science to develop a broad array of product offerings and features. The firm employs big data to revamp its job listings, “who’s viewed your profile”, and “who’s viewed your posts”. These offerings have brought millions of new customers to LinkedIn and have helped retain them as well.
- Using Big Data to refine a company’s core search and ad-serving algorithms. For example, Google is continually developing new products and services that have big data algorithms for search or ad placement at the core, including Gmail, Google+, Google Apps, and others.
- BIRD can provide key insights using medical data, regarding the previous medical history of patients, hospital chains can provide better and quick service. This in turn would help them prepare for area specific emergency deployment and warn governments of potential epidemics through quick identification of common symptoms across patients in their distributed network of databases through efficient AI and automation that would further reduce organizational costs with respect to diagnosis and prognosis procedures.
- Virtual testing can be seamlessly achieved using simulated what-if-scenarios built in BIRD’s Neural Networks and Machine learning algoritms. In 2018 it is quite evident that, if an organisation is serious about creating new products with big data then they should develop a process for testing these new products on a virtual scale before releasing them to customers.
Drive Faster and Better Business Decisions
BIRD has tremendous capabilities in providing Business Intelligence to influence Business Decisions and increase Business Efficiency. With the speed and effectiveness of the Hadoop and Kafka frameworks boasting features like in-memory analytics, combined with the ability to analyze new sources of data, businesses are able to analyze information immediately (in the span of seconds) – and make decisions based on what they’ve learned.
The primary purpose of traditional small data analytics was to support internal business decisions. They addressed questions such as: What offers will resonate with your customers? Which customers are most likely to churn? How much inventory should you be holding in the warehouse? What should be the price of your product during a particular season?
Previously, companies have been analysing only structured data sources that too pertaining to a single data base and not across a distributed network of data bases and servers in order to answer these questions.
However, today, a lot of data pertaining to customer information is unstructured such as data from social media, emails, customer calls, images, audio files, video logs etc.
The problem with analysing unstructured data is that it doesn’t have the sort of structure that one should usually expect for structured data, presented in the form of: tables of records with fields of meaning and connection between tables.
In the past, unstructured data couldn’t be analysed due to the lack of the advanced and robust big data tech softwares such as BIRD.
Now, with BIRD one can harness the capability to analyse unstructured data within seconds using natural language processing and machine learning techniques to identify customers who use words, phrases and actions that express satisfaction/dissatisfaction and then do some sort of intervention to identify its source.
Impact Cost Reduction
BIRD runs on data that are primarily within framework technologies such as Hadoop and Kafka along with cloud-based analytical capabilities using ML and AI to effectively bring about significant cost advantages when it comes to storing large amounts of data – plus it can identify more efficient ways of doing business.
If a business is seeking cost reduction, they should be familiar with the concepts of MIPS (millions of instructions per second—how fast a computer system crunches data) that can be enabled through BIRD, along with the fact that terabyte storage for structured data are now most cheaply delivered through big data technologies like Hadoop clusters (Hadoop is an open source software framework specifically built to process large amounts of data from terabytes to petabytes and beyond).
The cost of a Hadoop data management system, including hardware, software, and other expenses comes to less than $1000 a terabyte — which is negligible compared to other data management systems.
Thus, BIRD on Cloud promises a fruitful future by providing the right business intelligence at the tip of your fingers within the span of a few seconds; influencing you to make the right business decisions at the right time!
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