Companies of today need to embrace that data capital is a valuable asset with making key decisions in the company on competitive strategy level. It comes before financial investment on the developments of new services, products business processes. The digital data from their consumers offer better analytical insight on consumer facts with graphs. Every activity which involves digitization and datafication processes data from public, commercial to private sectors. In this article we’re going to look what big data means, why some consumers have concerns and how businesses profit from it.
All businesses are influenced by the following three laws of data capital: 1. Data comes from activity: for companies it’s important to record when and what happens at one time. You know your suppliers, partners and consumers better and look at your rivals up and down in the industry. 2. Data makes more data: through smart algorithms you can automatically improve your own performance on various area”s such as ad targeting, fraud detection, inventory management and drive pricing higher or lower. 3. Platforms tend to win: in every industry all of them compete to be the dominate platform for algorithmic services, because it all involves exploiting new and relevant information before your rivals.
Data capital doesn’t work the same as financial capital, because it can be used over and over again and in various ways. This multiple analytic or algorithmic investment cause the problem of endless data possibilities after the obvious highest priority of cutting costs and increasing revenue.
In order to discover new correlations and connecting to use, you can cut this opportunity space in two. The first mentioned is data market places where data scientists can shop for data sets to gain new perspectives on target customers and explore and discover fire wall mistakes. And secondly data liquidity: your company stores their data in different sections on different data bases. The costs of moving, manipulating an storing diverse data for fruitful answers/results will increase . The need these costs to go down by smart integration products exploiting low-costs, scale out and in memory technologies. These will nearly instantly convert data into new solutions for fraud detection, inventory management and fast-changing algorithmic pricing.
Big data is what you call a lot of data and we make every year more and more amount of data. Such as making online purchases and taking part of social media. It contains video’s, photographs, documents, tweets, social media posts, e-mails, financial transaction reports and many more. Every time you go online you leave a tail of data behind like you taking a walk on a beach. People make more use of different and cheaper WiFi or GPS devises, thus making it more accessible to various people form various backgrounds. It can all end in an unstructured sets of digitized data, but fortunately there are methods to collect, process, analyse and store it. Companies need to filter a vast amount of available data to keep up in their market and to prioritize what’s the is the most relevant matter in hand.
Fortunately, you don’t have to be a data scientist or need a team of programmers to crunch numbers, but you do need a basic understanding of the program. Software programs became faster and easier to operate with the help form cloud services such as Google analytics. It aims to find patterns and correlations that provide new insights to make cost efficient decisions. Some software services are that fare that they can predict if you are the right potential goal-group of the product. For example: how Target figured out a teen girl was pregnant before her father did.
Other examples are: governments can improve their policy decisions and services based on big data analysation of utility usage, crime rates, traffic patterns, average age in neighborhoods and other statistics. News outlets already make allot of use of big data for their trends, stories and other activities. After the NSA domestic spying revelations some people feel it’s disturbing what others have on information about them. It sounds like the Orwell’s big Brother. The government and privacy advocates regulates these activities and give the masses some control over what becomes public knowledge. Huge data sets can predict the weather, election rates, scientific and sociological research and other potential harm: outbreaks and natural disasters.
Experts in the big data field see a bright future for their industry: data volumes will increase with the growth of WiFi and devices, build-in intelligence of the future of the company, machine learning will grow, more companies hire data analysts and chiefs, algorithmic services will emerge and most companies will have some sort of data capital. These were a few examples of a large pool of future predictions. In conclusion: data capital is going to play an extensional role with (govern) businesses and especially for if they swim in high competitive markets. However, wherever your preferring lies is on government data collection is, know that machine made foretelling’s aren’t waterproof like the political elections outcomes of 2016/2017.
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