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Big Data Management Service for Business Transformation
For decades, companies were compromising with the data at higher rates due to the complexity, storage limitations, and storage cost. Sometimes, this compromise worked fine. Gradually, companies started to understand the importance of data and how to deal with it, and the concept of Big Data Management Services was raised. With the advancement in technology, there are very few issues in managing the storage limitations and complexity of the data.Big Data Strategies include the best way of handling the numerous amount of data that involves the process of storing, analyzing the huge set of information. Click to explore about our, Big Data Strategies with Advanced Analytics
Let us show you how complex data is.
In 2003, Nokia released the 1100 mobile phone. The information needed to save a contact on that phone was very little, and there was no facility to take the automatic backup of the data. But now, in the era of smartphones, we can add email IDs, photos, URLs, an alternate number, etc. We can opt for an automatic backup. In the case of the iPhone, the data saved on the cloud includes photos, songs, notes, drawings, text, email ID, fingerprints, face scans, and many more types. IDC research predicts that the ‘Digital Universe’ (i.e., the data created and traced each year) can grow to be ~180 zettabytes, and ~50 percent of the world's data can be on the public cloud in 2025 (from~3 zettabytes in 2012). With time, new and additional kinds of knowledge are generated at a massive pace daily. To know the dimensions of knowledge flow within the length of sixty seconds on the web in 2018:- 187 million emails were sent
- YouTube videos watched were 4.3 million
- 3.7 million Google searches were performed
- WhatsApp messages exchanged were 38 million
Big Data Security is the collective term for all the measures and tools used to guard both the data and analytics methods from attacks, theft, or other malicious activities. Click to explore about our, Big Data Security Management
What is Big Data Management?
The streamlined management of structured and unstructured data silos, along with all the tools used in the Big Data environment of an organization, is known as Big Data management.How Big Data Management Benefits Your Business?
The management of Big Data is benefitting businesses in various manner. The highlighted points given below is just an insight into it:
- Cost-Saving - Companies can cut their costs by analyzing the data and stop investing in operations that are not profitable.
- Client Engagement - It helps in better client service by analyzing the behavior of the clients.
- Accurate View of Data - Big data analytics provide you with a precise view of data since the data is gathered through multiple sources. Hence, there is no possibility of inaccurate data. Making business decisions based on incorrect or incomplete data can cost a fortune to your business. For example, in the travel industry, profit driven from customer satisfaction. To launch a new offer, the company needs to measure the behavior trends of customers as well as the market trends.
- Predictive Future Analysis - It keeps you updated by predicting future trends. AI/ ML can help in reducing the risk.
- Increase in Revenue - In a survey, 65 percent of participants stated that data management has helped in their business growth.
- Competition Analysis - Big data management quality analytics can help you in analyzing your competitors, and with the help of those results, you can outperform your competition.
A part of the Big Data Architectural Layer in which components are decoupled so that analytics capabilities may begin.Click to explore about our, Big Data Ingestion
Why do we need Big Data Managed Services?
There are a plethora of factors that are leading to the need for Big Data Managed Services, which are as follows:- Lack of Talent - There is not enough talent in the market who can manage Big Data. One can not put a new resource on the management of Big Data. As perIndeed.com, the current average salary for a data scientist is $121,455, while a data warehouse engineer typically makes $110,763.
- Preeminent Security - Due to multiple data sources, the risk factor increases. There is no guarantee that all the channels/data collected will not contain any malware/virus or any other security threat.
- Technology Whirlwind - Several tools are available in the market, and many more are coming. It is tough always to be updated and ready for the technology shuffling.
- Sustained delivery - Continuous functioning of the Big Data is one of the critical factors, and it can be disturbed by many instances like network failure, low storage space pending updates or patchwork, etc.
- Business insights - Real-time business insights are critical to analyzing business outcomes. However due to the lack of resources, many organizations are not able to implement/get the correct sights of the data from their environment.
- Data management - Several big complexes, structured and unstructured datasets stored in different locations. Moving that to a single site or third-party service provider raises security and compliance concerns.
New technologies in Big Data Analytics are changing continuously.Click to explore about our, Latest Trends in Big Data Analytics
Role of Big Data in Different Industries
Let's explore the effect of Big Data by taking a glance at some key industries to know how data is leading to performance-driven and competitiveness.Big Data in Retail
Whether it is a physical or online store, a retailer wants to keep the customer on the floor for a longer time, and it can only be possible if a customer is in a buying mood. With the help of big data analytics, retailers can predict customer behavior and offer the things in store as per their choice or trends. For example - Amazon is extensively using data science in Big Data for customer behavior.Big Data in Healthcare
There are many benefits of using Big Data in the medical industry. Hospitals can reduce waiting time by analyzing patient visits. Researchers can predict disease patterns easily; this analysis could help in taking advanced safety measures. With the data analysis of a patient’s medical tests, doctors can even predict the chances of a person suffering from a disease in the future. IoT Big Data is the technology we can use for the continuous collection of data.Big Data in Manufacturing
It can help in optimizing production by predicting machine failures and reducing downtime, which will result in efficiency, speed, and cost reduction. Big Data in Manufacturing can help in trends of cost up-down in raw materials. It can also help in increasing the ability of the supply chain of an organization. For example - By using predictive analysis, Intel is saving millions of dollars on a single production.Big Data in Banking/ Finance/ Insurance
The significant advantages of Big Data in BFSI are fraud detection and faster transactions. Big Data analytics helps in reducing errors, and by understanding customer behavior, we can offer them more personalized solutions.Big Data in Transportation
The travel industry plays a vital role in the world economy. Weather analysis is helping to reduce the late arrivals. By analyzing the events of equipment failure, we can predict the upcoming failure in cars, trains, and planes. It can help in saving lives, money, and time.Big Data in Telecom
Big data helps in forecasting network congestion issues and helps in smooth and continuous delivery. It also helps in fraud detection, enhancing security and customer experience.Big Data in Media
Big data predictive and real-time analytics provide a global view of customer insights. It helps in personalized marketing and media content usage analysis. The best example is Netflix.Big Data Platform focuses on providing their user with efficient analytics tools for massive datasets.Click to explore about our, Big Data Platform
XenonStack's Big Data Management Services Offering
Data in business is like a queen in chess. Working as your extended Big Data Team, our Experienced Data Scientists and Big Data Experts team will simplify each step in engagement. Along with Data Cleaning, Hadoop Management, or NoSQL handling, the following are our essential services:-Our Commitment
- 24*7*365 Support Service
- Dedicated and Certified Resources
- Configuration and Asset Management
- Network and Workload Management
- Data Backup and Disaster Recovery
- Data Acquisition, Processing, and Management
- Predictive Analysis
- Administration and Monitoring
- Patch and Update Management
- Expert Advice
We provide fully customizable SLA and subscription models. To learn more about, end to end managed services, you are advised to look into the below steps:
- Get in Touch with us for Big Data Analytics Services and Solutions.
- Discover more about our Big Data Security Tools
- Explore more about Enterprise-ready Big Data Managed Service Offerings.
