The Power of Big Data in Software Analytics and Decision-Making
Daily, your customers generate a wealth of data about themselves – whether opening your email, tagging you on social media or visiting your store or purchasing one of your products.
Business can find Big Data overwhelming; it consists of large sets that are hard to manage with traditional software and known by its volume, velocity, variety and veracity. It is defined by these parameters.
The data revolution has given managers unprecedented insights into their businesses, leading them to make better decisions and experience greater performance gains.
Every action taken by your employees, customers, vendors and partners creates data – be it emails, texts and social media updates; emails sent directly by customers to vendors; images and videos uploaded directly from cameras; readings from sensors; the locations of phones computers tablets as well as conversations held with virtual assistants – etc.
Information created daily is immense and often so complex that traditional databases and processing software simply cannot keep up. These massive sets of digital information, known as big data, reveal patterns, trends, associations related to human interactions and behaviors.
Over time, technology to address big data has matured and become more cost-effective. Hadoop, for example, is a popular open source framework that uses commodity hardware and software tools to collect and organize massive datasets efficiently while also offering real-time analytics that are vital for businesses that rely on data-driven decisions.
Spotify is one of the many companies taking full advantage of big data. They use it to recommend songs based on an individual’s likes and listening history, and also analyzes their 96 million user data to identify new opportunities such as adding live radio features or curating playlists.
Big data in analytics offers managers tremendous power by enabling them to measure a much wider array of measurements than previously possible, thus giving them more knowledge about their businesses – knowledge which translates directly into improved decision making and performance.
Volume is one of the five Vs that companies should focus on when considering data management strategies, and includes any data generated and moved around constantly – from social media feeds and sensors on smart products for instance).
Velocity refers to the rate at which data is produced and delivered to its destination. For instance, sales and marketing teams need access to timely streams of consumer data so they can act accordingly – otherwise, information will become outdated before it even reaches them!
Variety refers to the wide array of sources from which big data can be sourced and its many formats. This may range from smartphone clickstreams and in-house data to social media chatter and stock ticker updates; ultimately it is essential that business data come from sources pertinent to the individual needs of your industry.
Today’s businesses must move beyond simply collecting information and running analytics; they must take an active approach to decision-making using big data. Big data helps organizations work faster, remain agile and make more informed decisions that lead to business expansion and increased revenues.
Big data analytics enables businesses to recognize trends, patterns and correlations that would go undetected using traditional analytical software alone. It enables them to identify risks, automate processes and make strategic policies based on facts rather than intuition or past personal experience.
The three V’s of big data are volume, variety and velocity. Volume refers to the massive amounts of information businesses must process on an ongoing basis while velocity measures how fast information streams into an organization from sources like application logs, networks and social media sites or sensor-enabled equipment.
Information can be utilized from big data to identify new business opportunities, enhance customer service delivery and make more effective marketing decisions. Furthermore, big data analysis can also be used to develop strategies for risk management, customer retention and more by eliminating biases common in traditional business intelligence solutions. By helping companies recognize problems before they arise and concentrate their resources on areas which will increase profits quickly while understanding customer desires to provide personalized products and services, big data allows companies to identify problems before they happen and focus on growth initiatives more quickly than before.
Creating a Plan
Big data refers to large volumes, velocity and variety of information assets that require cost-effective innovations for processing in order to enable greater insight, decision making and process automation. Volume is defined as the sheer volume of information being created; businesses manage approximately three million pieces daily which double approximately every 40 months.
Velocity of Big Data is also key; having real-time access to it can be invaluable when analyzing customer behavior or planning marketing campaigns, for example. A retailer could use analytics to assess whether their store would fit well into a new location by looking at sales trends and demographic data of the area where it would open. Furthermore, veracity should never become so significant that conclusions cannot be drawn accurately from big data analysis.
Big data’s true power lies in turning its raw form into insights that lead to improved business decisions and performance, through various analytical techniques that utilize familiar statistical correlation methods applied over greater datasets. This may involve filtering web logs for analysis of ecommerce behaviors; gathering sentiment analysis through social media interactions; or building predictive models to predict future product or service needs.