Today, the term “big data” is more than just a buzzword in the business world. It is a driving force behind growth and innovation as business leaders utilize Big Data to promote sales through informed decision-making. From major manufacturers and tech giants to Juicy Stakes casino entertainment venues and mom-and-pop eateries, people in business are coming to understand how they can leverage big data analytics to gain insights and make informed decisions that drive business to their sites.
Big Data
Big data is data that involves large, complex data sets that allow businesses to address business problems that weren’t addressable before. These data sets contain more volume, have more velocity, and contain more variety than traditional data sets.
The technology that makes big data available allows for the processing of high volumes of data including the large quantities that come from social media feeds, clickstreams on a mobile app or sensor-enabled equipment. The information, which comes from both unstructured and semi-structured data types (audio, video, text, etc) is analyzed quickly so that businesses can produce more efficiently and develop new products.
With today’s increased, cheaper, and more accessible volume of big data, businesses can now make more accurate and precise business decisions.
Finding value in big is a discovery process that requires business users, executives, and insightful analysts who recognize patterns, ask the right questions, predict behavior, and make informed assumptions.
Most big companies today use big data to anticipate customer demand by building predictive models for new products and services. They classify products’ key attributes and model the relationship between those attributes and the offerings’ commercial success. Proctor & Gamble, for instance, uses analytics and data from social media, early store rollouts and test markets to plan, produce, and launch new products.
Ways that Big Data Can Be Used
Big Data can be used to:
- Enhance customer experience. Through big data, businesses can get a clearer view of customer experience by gathering data from web visits, call logs, and social media. These, as well as other sources, can be analyzed to improve the interaction experience and then maximize the value delivered through reduced customer churn, personalized offers, and proactive action when needed to handle issues.
- Bolster security. The use of big data can help identify patterns in data that may point to fraud. By aggregating large volumes of information, regulatory reporting becomes much easier, security landscapes can be navigated more smoothly and it’s easier to protect the business from cybercriminals and rogue hackers.
- Maximize predictive maintenance. Factors that can predict mechanical failures are often deeply buried in structured data. By analyzing millions of log entries, error messages, sensor data, structured data such as the year, make and model of equipment, engine temperature data, and error messages, the business can identify potential issues and deploy maintenance in a more cost-effective manner.
- Promote machine learning. Big data is one of the reasons that machine learning is front and center in today’s business world. Being able to teach machines instead of programming them means that big data is needed to train machine learning models.
- Innovate drive. By studying interdependencies among institutions, entities, and humans, big data can help businesses innovate by examining new ways to use those insights. Data insights can be used to improve decision-making about planning and financial considerations, to examine trends, and to determine what customers are looking for (i.e. dynamic pricing, etc).
- Maintain operational efficiency. Using big data, business leaders can analyze and assess production, customer returns, feedback, and other factors to anticipate future demands and reduce outages. Businesses can also use big data to improve decision-making in line with current market demand.
How Does Big Data Work?
Big data in today’s world has its challenges. For one thing, it’s challenging to keep pace with the huge data volumes that are doubling in size every 2 years, not only to store that data but to analyze it meaningfully. Data scientists say that 50 to 80 percent of their time is spent curating and preparing data before it can actually be used.
Still, the drive to access big data is growing because overall, businesses can see the results. Businesses use big data to gain new insights that open up new business models and new opportunities. To this end, after collecting the data, the goal is to integrate it, manage it, and analyze it.
Integrate
Big data brings together data from many disparate applications and sources. Traditional data integration mechanisms, including load (ETL) will extract and transform but can’t analyze the data at the scale that’s needed. During the integration stage, the data needs to be obtained, processed, and formatted in a way that a business analyst can move forward.
Manage
There are a number of storage solutions, including both cloud storage and hardware storage but the storage must meet basic storage
Analyze
The investment in big data pays off when the data is analyzed and when the business acts on that data. If the data is voluminous and varied enough it’s possible to get new clarity with a visual analysis to make important discoveries. Once data models are built with machine learning and artificial intelligence it’s time to put that data to work.
To help you on your big data journey, we’ve put together some key best practices for you to keep in mind. Here are our guidelines for building a successful big data foundation.
Best Practices
If you’re ready to move ahead with the investment in working with big data, you need to keep a few things in mind.
- Align big data with specific business goals. As you move through the findings that big data brings you, you’ll make new discoveries. Those discoveries can be used for decisions on new investments in organization, infrastructure, and skills so that you guarantee ongoing funding and project investments. You should be asking yourself how big data will support and enable your top IT and business priorities – learning how to filter web logs to understand e-commerce behavior, understanding statistical correlation methods and their relevance, deriving sentiment from customer support and social media interactions, etc.
- Use standards and governance to ease skills shortage. This means that you add decisions about big data tech, decisions, and considerations to your IT governance program. By standardizing your approach you’ll be better able to leverage resources and manage costs. proactively identify any potential skill gaps through hiring new resources, training/cross-training existing resources, and leveraging consulting firms.
