Big data analytic is high analytic techniques operate on big data sets. Big data analytic is really about two things big data and analytic plus how the two have teamed up to create one of the most fundamental trends in business intelligence (BI) present. By defining advanced analytic, then move on to big data and the combination of the two."There is little doubt that the quantities of data now available are indeed large, but that’s not the most relevant characteristic of this new data ecosystem.
Features of Big Data
1. Volume : The quantity of generated and stored data. The size of the data determines the value and potential insight- and whether it can actually be considered big data or not.
2. Variety : The type and nature of the data. This helps people who analyze it to effectively use the resulting insight.
3. Velocity : In this context, the speed at which the data is generated and processed to meet the demands and challenges that lie in the path of growth and development.
4. Variability : Inconsistency of the data set can hamper processes to handle and manage it.
5. Veracity : The quality of captured data can vary greatly, affecting accurate analysis.
Advantages of Big Data:
1. Big Data is Timely : 60% of each workday, knowledge workers spend attempting to find and manage data.
2. Big Data is Accessible : Half of senior executives report that accessing the right data is difficult.
3. Big Data is Holistic : Information is currently kept in silos within the organization. Marketing data, for example, might be found in web analytics, mobile analytics, social analytics, CRMs, A/B Testing tools, email marketing systems, and more… each with focus on its silo.
4. Big Data is Trustworthy – 29% of companies measure the monetary cost of poor data quality. Things as simple as monitoring multiple systems for customer contact information updates can save millions of dollars.
5. Big Data is Relevant – 43% of companies are dissatisfied with their tools ability to filter out irrelevant data. Something as simple as filtering customers from your web analytics can provide a ton of insight into your acquisition efforts.
6. Big Data is Secure – The average data security breach costs $214 per customer. The secure infrastructures being built by big data hosting and technology partners can save the average company 1.6% of annual revenues.
7. Big Data is Authoritive – 80% of organizations struggle with multiple versions of the truth depending on the source of their data. By combining multiple, vetted sources, more companies can produce highly accurate intelligence sources.
8. Big Data is Actionable – Outdated or bad data results in 46% of companies making bad decisions that can cost billions.
Scope of Big Data :
The world is becoming data driven. Each and every decisions are now taken on data from stock markets to machines that stalk you.
The data generated is growing exponentially, with this data we can also develop a great solutions around the data.
The big data market is predicted to reach $16.1 billion in 2014, according to IDC (International Data Corporation). Though Big Data can increase productivity and profitability for companies, implementation is a challenge. In addition, there are various challenges in collecting, organizing, analyzing and deriving insights, such as
1. Big Data in Multiple formats.
2. Structured / Unstructured.
3. Data Size.
4. Velocity at which the data gets generated.
5. Accuracy and integrity of the data collected
Scope has partnered with various organizations to create customized Big Data solutions, keeping in mind the direct and indirect needs of businesses. Scope has created cloud-based Big Data Solution for small and medium-sized enterprises, which has eliminated the need for a dedicated Big Data Infrastructure.
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