Digital technologies are unlike any others – they change everything businesses do. That’s why, as this research confirms, digital jobs and activity are becoming ever more important in apparently non-digital industries.
INTRODUCTION TO BIG DATA
Big data is is a term for data sets that are so large or complex that traditional data processing applications are inadequate to deal with them. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization, querying, updating and information privacy. The term "big data" often refers simply to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. "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.
Is high-volume, high-velocity and/or high-variety information assets
that demand cost-effective, innovative forms of information processing
that enable enhanced insight, decision making, and process automation.
5V of Big Data
Volume
Organizations collect data from a variety of sources, including business transactions, social media and information from sensor or machine-to-machine data. In the past, storing it would’ve been a problem – but new technologies (such as Hadoop) have eased the burden.
Velocity
Data streams in at an unprecedented speed and must be dealt with in a timely manner. RFID tags, sensors and smart metering are driving the need to deal with torrents of data in near-real time.
Variety
Data comes in all types of formats – from structured, numeric data in traditional databases to unstructured text documents, email, video, audio, stock ticker data and financial transactions.
At SAS, we consider two additional dimensions when it comes to big data:
Variability
In addition to the increasing velocities and varieties of data, data flows can be highly inconsistent with periodic peaks. Is something trending in social media? Daily, seasonal and event-triggered peak data loads can be challenging to manage. Even more so with unstructured data.
Complexity
Today's data comes from multiple sources, which makes it difficult to link, match, cleanse and transform data across systems. However, it’s necessary to connect and correlate relationships, hierarchies and multiple data linkages or your data can quickly spiral out of control.
Why Is Big Data Important?
The importance of big data doesn’t revolve around how much data you have, but what you do with it. You can take data from any source and analyze it to find answers that enable 1) cost reductions, 2) time reductions, 3) new product development and optimized offerings, and 4) smart decision making.How It Works
data in e-commerce we make it become money
Before
discovering how big data can work for your business, you should first
understand where it comes from. The sources for big data generally fall
into one of three categories:
Streaming data
This category includes data that reaches your IT systems from a web of connected devices. You can analyze this data as it arrives and make decisions on what data to keep, what not to keep and what requires further analysis.
This category includes data that reaches your IT systems from a web of connected devices. You can analyze this data as it arrives and make decisions on what data to keep, what not to keep and what requires further analysis.
Social media data
The data on social interactions is an increasingly attractive set of information, particularly for marketing, sales and support functions. It's often in unstructured or semistructured forms, so it poses a unique challenge when it comes to consumption and analysis.
The data on social interactions is an increasingly attractive set of information, particularly for marketing, sales and support functions. It's often in unstructured or semistructured forms, so it poses a unique challenge when it comes to consumption and analysis.
Massive amounts of data are available through open data sources like the US government’s data.gov, the CIA World Factbook or the European Union Open Data Portal.
After identifying all the potential sources for data, consider the decisions you’ll need to make once you begin harnessing information. These include:
How to store and manage it
Whereas storage would have been a problem several years ago, there are now low-cost options for storing data if that’s the best strategy for your business.
Whereas storage would have been a problem several years ago, there are now low-cost options for storing data if that’s the best strategy for your business.
How much of it to analyze
Some organizations don't exclude any data from their analyses, which is possible with today’s high-performance technologies such as grid computing or in-memory analytics. Another approach is to determine upfront which data is relevant before analyzing it.
How to use any insights you uncover
The more knowledge you have, the more confident you’ll be in making business decisions. It’s smart to have a strategy in place once you have an abundance of information at hand.
Key Success of E-Commerce
- Providing competitive price
- Providing purchasing services that are responsive, fast, and friendly.
- Providing information on goods and services that are comprehensive and clear.
- Provide many bonuses such as coupons, special offers, and discounts.
- Give special attention such as the proposed purchase.
- Providing a sense of community for discussion, feedback from customers, and others.
- Made trading
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