/jktzf54w90k-Big data is rapidly growing, diversified data sets. The “three v’s” of big data—volume, velocity, and variety—cover the data points. Data mining produces multi-format big data.
- Big data is a large amount of diversified information arriving faster and faster.
- Unstructured big data is less measurable and more free-form.
- Extensive data analysis can benefit most company departments, but managing clutter and noise can be difficult.
- Big data can be acquired via publicly shared comments on social networks and websites, freely collected from personal devices and apps, questionnaires, product transactions, and electronic check-ins.
- Big data is usually kept in databases and analyzed using software specialized for massive, complicated data sets.
Big Data Works:
Structured or unstructured big data. Structured data is numeric and handled by the organization through databases and spreadsheets. Unstructured data is not ordered or formatted. Social media data helps organizations understand client demands.
Big data can be acquired via publicly shared comments on social networks and websites, freely collected from personal devices and apps, questionnaires, product transactions, and electronic check-ins. Smart gadgets’ sensors and other inputs enable data collection in many situations.
Big data is usually kept in databases and analyzed using software specialized for huge, complicated data sets. SaaS companies specialize in managing complex data./jktzf54w90k.
Big Data Uses:
To find correlations, data analysts examine demographic and purchasing history data. In-house or third-party big data processing experts can conduct such analyses. Such professionals help businesses turn huge data into actionable knowledge.
Alphabet and Meta (previously Facebook) employ big data to target social media and web users for ad revenue.
Human resources, technology, marketing, and sales can use data analysis results. Big data aims to speed up the product launch and save time and resources needed to obtain market adoption, target audiences, and customer satisfaction.
Big Data Pros and Cons:
- Data growth brings opportunities and challenges. More data on customers and prospects should help organizations customize products and marketing to maximize consumer happiness and repeat business.
- Large data collectors can perform richer analyses for all parties.
- With the quantity of personal data available to individuals nowadays, corporations must take precautions to secure this data, which has become a hot debate in today’s internet world, especially after the many data breaches companies have encountered in recent years.
- Big data improves analysis, but it may also overload and clutter it. Companies must handle more data and distinguish signals from noise. Data relevance is crucial./jktzf54w90k.
- Data may need special treatment before being used. Numeric data is easily stored and sorted. Emails, movies, and text documents may require more advanced procedures to be useful.
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Big Data: Management Revolution:
Tamar Cohen, Happy Motoring, 2010, silkscreen on an old road map, 26′′ x 18′′
Measure what you manage-/jktzf54w90k.
That W. Edwards Deming and Peter Drucker quote explains why the recent growth of digital data is so crucial. Big data allows managers to better measure and understand their firms and improve decision-making and performance.
Consider retail. Physical bookstores could track which books are sold. They could associate some purchases with customers if they established a loyalty program. That’s all. However, online buying greatly improved customer knowledge. Online retailers may track what customers bought, what else they looked at, how they browsed the site, how much promotions, reviews, and page design influenced them, and commonalities among people and groups.
They soon created algorithms to anticipate what books users would like to read next, improving with each response or rejection. Traditional shops couldn’t get this information or act on it quickly.
Amazon has bankrupted numerous physical bookstores.
Amazon’s familiarity almost dulls its force. Born-digital enterprises should achieve things that company executives could only dream of a generation ago. Big data can also transform established enterprises. It may give them more competitive advantages (internet businesses have traditionally competed on data understanding).
As discussed, this revolution’s big data is much more powerful than previous analyses. We measure and manage better than ever. We can forecast and decide better. We can target more-effective solutions in areas where instinct and intuition have ruled instead of evidence and rigor./jktzf54w90k.
Big data tools and ideologies:
Big data tools and ideologies will revolutionize how we see experience, competence, and management. Big data is a management revolution for smart industry leaders. As with any major business shift, becoming a big data–enabled firm requires hands-on—or hands-off—leadership. However, bosses must adapt now.
“Isn’t ‘big data’ just another word for ‘analytics’?” question business executives. They’re related: Big data, like analytics, tries to gain commercial advantage through data insight.
Three major distinctions exist:
In 2012, 2.5 exabytes of data were created daily, doubling every 40 months. More data is being transferred per second than was kept on the internet 20 years ago. This allows firms to work with many data types in one package, not just internet data. Walmart’s customer transactions generate 2.5 petabytes of data per hour. One petabyte equals 20 million file cabinets of text. One billion gigabytes is an exabyte.
Many applications value data production speed over volume. Real-time or near-real-time information makes a corporation more agile than its competitors. Alex “Sandy” Pentland and his team at the MIT Media Lab used mobile phone location data to estimate how many people were in Macy’s parking lots on Black Friday, the start of the US Christmas shopping season./jktzf54w90k.
This allowed the retailer’s critical day sales to be estimated before Macy’s reported them. Wall Street analysts and Main Street managers can gain a clear edge from such rapid insights.
Social media posts, sensor measurements, cell phone GPS signals, and more are big data. Many key large data sources are new. Twitter was founded in 2006, and Facebook in 2004. Smartphones and other mobile devices generate massive amounts of data about people, activities, and places. The iPhone was released five years ago, and the iPad in 2010.
Thus, structured databases formerly contained most business data are unsuitable for big data storage and processing. At the same time, the continually dropping costs of all computing components—storage, memory, processor, bandwidth, etc.—mean that data-intensive approaches are becoming cost-effective.
New sources of information:
New sources of information and cheaper equipment are bringing us into a new era of abundant digital knowledge on nearly every business topic. Online commerce, social media, GPS, mobile phones, and instrumented machines generate massive amounts of data. Everybody generates data now. There is a lot of signal in the noise in unstructured, unorganized data. Big data makes decision-making simpler and more powerful. “We don’t have better algorithms,” says Google’s research head Peter Norvig. More data.”/jktzf54w90k.
Data-Driven Companies Perform:
Sceptics may also ask, “Where’s the evidence that using big data intelligently will improve business performance?” Anecdotes and case studies of data-driven success abound in the business press. We suddenly realized that nobody was rigorously addressing the question.
We led a team at the MIT Center for Digital Business alongside McKinsey’s business technology division, Wharton’s Lorin-Hitt, and MIT doctoral student Heekyung Kim to close this humiliating gap./jktzf54w90k.
We hypothesized that data-driven companies would outperform. We collected performance data from annual reports and other sources and conducted structured interviews with CEOs at 330 public North American corporations regarding their organizational and technology management strategies.