There’s no debating the importance of data for businesses. From understanding customer behavior to onboarding new employees to creating effective marketing strategies, data can influence and inform virtually every aspect of an organization. But, the downside to collecting and using data is the sheer amount of it which can put a strain on a company’s data management processes. An organization may find itself struggling to keep up with processing power, storage capacities, and network performance as its data grows exponentially.
Fortunately, there are solutions to address the pain points of big data analysis, which we’ll dive into later in this article. But first, let’s take a closer look at the challenges that arise when collecting and managing big data.
- Disintegrated data sources
Handling an influx of massive data coming from different sources can be overwhelming, but unfortunately, this is the nature of collecting data across an organization. Trying to sort and filter out the right data could take weeks or months (or longer) and require an army of data scientists and engineers. When a business needs to make real-time decisions or proactively address a challenge, a slowdown could result in missed opportunities, disgruntled customers, or decreased sales.
- Ineffective data classification
Before you can make sense of your data, such as identifying patterns or trends, you have to get all of it into one place to analyze it. Without the right tools, this can mean manually cobbling together data from different places into a spreadsheet or similar platform. Not only is this time consuming but it’s ripe for errors. Any time a task is manually handled by a human, there is a chance (or even likelihood) that mistakes will be made. And if data is being pieced together from multiple sources, the chances of inaccuracies and errors increases. This could mean making decisions or setting strategies based on inaccurate data.
- Lack of context
Another critical part of analyzing data is understanding its context. Data without context is open to different misinterpretations, misunderstandings, and reaching the wrong conclusions. By definition, “contextualization” means adding related information to something in order to make it more useful. When applied to data, this can mean understanding the timeframe or previous benchmarks for a particular data set. This context can make finding correlations, patterns, and trends easier.
- Complicated reporting
To make data actionable, it’s critical to be able to present it to decision makers in a clear and precise way. Without that, you’re just presenting a random smattering of numbers, graphs, and charts. Many organizations use tools that require cumbersome and overly complicated reporting for each data insight that doesn’t make actionable decision making easy. Precious time and resources could be wasted producing reports that aren’t useful, don’t tell a clear story, and take too much time to create.
The solution: one single platform
Now that we have a better understanding of the challenges that can arise during big data analysis, let’s look at some solutions – actually, one solution.
At Gemini Data, we’ve created a platform that addresses and solves all of these problems in one place. By connecting the dots between data from disparate sources, our tools help organizations effectively transform data into stories. Rather than struggling to organize disintegrated data sources, pulling data together into one spreadsheet, and creating ineffective reports, Gemini’s platform allows businesses to seamlessly integrate multiple data sources, quickly manage and correlate data, and tell better data stories.
With one platform, you get three tools to solve your biggest data challenges:
- Gemini Explore transforms data analytics by enabling anyone to easily and intuitively interact with data using contextual storytelling. It’s all about simplifying and making it easier to see, understand, and communicate the complex – so people can learn faster and do their jobs better.
- Gemini Stream allows organizations to seamlessly collect, reduce, transform, parse, and route machine data from and to the most common Big Data platforms, using a single interface.
- Gemini Central provides a state-of-the-art turnkey solution for your analytics needs as it is integrated and pre-configured with a lightweight OS and other management tools and applications. It’s an innovative and robust platform that preempts the need to implement tricky and complex hardware specifications, capacity sizing, OS, IP and other configurations.
Not only does Gemini help mitigate some of the biggest big data analysis challenges, it has multiple use cases across many industries. From insurance fraud detection to cybersecurity alert triage to investment prospecting, Gemini can help your business connect the dots and get to insights faster.
If you’re experiencing challenges in your big data analytics, reach out to Gemini today to see how we can help your business.