It is hardly discussed today that business intelligence is beneficial to any organization, regardless of industry. Data governance and optimization have been shown to lead to better decision making in the long run.
That doesn't mean the data implementations have been perfect. Some companies have failed in their efforts to become data-driven on a much larger scale than might be expected. Others, however, are hurrying up and have started using external data sources en masse.
Big data has been incredibly useful for those who have successfully managed their internal sources. Strategic use of big data enables organizations to better understand their customers, create more engaging marketing campaigns, and forecast demand more accurately.
Big data and external sources
Following the model of the five Vs, two of the key determinants, important in our case, are volume and speed. Big data derived from external sources is different from internal, because it has no limit.
Internal sources will always be pre-limited by the size of the company. In a poetic sense, the company itself is at the mercy of its customers to obtain that data. If the organization is small in both operations and revenue, not much data will be produced. Trying to gain big insights from small data sets is often a recipe for failure.
External sources, however, are limited by the rate of data production on the Internet. In practice, the speed and volume of data are practically unlimited, only restricted by technical capabilities. There is so much information being produced on a daily basis that evend analyze.
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As such, both the volume and velocity of big data, primarily from external sources, are magnitudes greater than internal resources would allow. In addition, there is an important qualitative difference in the data.
External sources provide us with remaining data from a wide variety of different sources. Most of it has no direct relationship with the business that will use that information, which makes it much more unbiased than anything an internal source might produce.
In the end, a combination of both sources produces great data. The external ones, however, play a much higher volume and speed. It is important to note that these two sources are complementary. While some of the insights they provide may overlap (such as customer habits), they can also offer unique signals that can help improve your overall trading strategy.
Hidden gems of BI in big data
External sources may not always produce unique signals that make us change our strategy, but they strengthen our existing methods. In addition, they can provide information that would not otherwise be available.
Take the use of CRM, for example. Almost all digital businesses use these systems in their daily operations. Customer profiles, however, have expanded in many directions. Potentially useful data is now available on companies and individuals scattered throughout the web.
Social media is a great example. Many businesses may choose to pull publicly available data from social sources, as most of their customers will have some sort of presence. These enrichments would be particularly useful for those who work in B2B.
On the other hand, a combination of internal and external sources can create better planning and budgeting options for all businesses. External data allows organizations to predict and forecast demand, while internal sources can more accurately represent the resources available to meet those needs.
It is especially useful for industries like e-commerce. External data gives organizations a glimpse of a better overview of the entire market, its trends and possibilities. Companies have successfully used various methods to collect and access large amounts of external data.
acquire big data
Since most digital companies successfully collect a large amount of data from internal sources, there is often no problem with its acquisition. The other counterpart, external data, however, is more complicated.
It can be separated into two distinct categories: traditional and advanced. Traditional external data (ie government reports, statistical databases, etc.) has been used primarily by financial firms and large e-commerce companies. These are usually huge data sets that provide informative information.