What can automated data analytics do for you?
Automated Analytics is key to unlocking the value of big data
In a world where everything from wearable technology to “smart home” devices is connected to the Internet, data is everywhere, and more information about trends in consumers’ habits and preferences is available now than ever before. But what can this data be used for, and how can automating its analysis help your organization?
Why analyze data?
Essentially, automated data analytics is automatic decision making based on data—and not just any data: big data. Big data isn’t simply about quantity. It refers to data that comes from multiple sources, exists in many forms and requires different types of analysis to gain insights from. The increasingly affordable collection and storage of big data presents revenue-raising opportunities for companies that can harness it to understand the status of their organization in real-time, from monitoring the effectiveness of marketing campaigns to forecasting areas of growth.
Barriers to effective data analysis
To analyze this explosion of data, organizations need tools that are robust, reliable and capable of being automated. Predictive analytics tools can manage big data, measure current trends and see where they might be heading, providing valuable insight for business leaders—assuming they can analyze that data quickly and efficiently enough to benefit from it. Tools like Hadoop and Azkaban are effective for creating models and running simulations, but often still require heavy manual involvement.
Sometimes, however, big data is just too big to analyze manually. Data lakes contain vast amounts of information from many sources, but useful patterns are hidden by the sheer volume of data and number of potential analyses to run. On the other hand, data can also be too spread out and isolated in silos, which occur when different parts of an organization have their own data sources that aren’t shared, and are another barrier to effective analytics.
Automated solutions can improve your business intelligence
When dealing with this much data spread across an organization, manual analysis is slow and prone to errors. By contrast, automated systems keep the data analysis process running without a hitch, so you can get straight to the data to reveal usable insights. Automated data analytics, for example, can break down old barriers by automatically compiling data from different sources and converting them to the same format, preventing new silos from forming and making the most up-to-date data accessible to everyone who needs it.
Automated data analytics is essential for keeping track of the many sources of data modern organizations use today, ensuring data scientists don’t waste time working with bad, out-of-date, or incomplete data. With a more streamlined data analysis process, important opportunities can become apparent, introducing agility to big data analysis and, ultimately, increasing your organization’s business intelligence and competitive edge.