Big Data

What Is Big Data?

Big data is a term applied to data sets whose size or type is beyond the ability of traditional Big-Datawords-768x656-minrelational databases to capture, manage, and process the data with low-latency.

Think of data before it is aggregated (and often partially discarded) and placed into a data warehouse. This can be data about customer interactions, data from sensors, web data, and a vast array of other sources.

Data in its raw form is often big data. It’s usually unstructured and very granular data that needs to be processed, cleaned, and aggregated before it is useful to traditional BI tools.

The problem is that these processes tend to fundamentally change the data, and often, these changes make data less useful for analytics. Once the changes are committed to the data warehouse, those changes are forever in-place.

“You cannot build a competitive advantage by analyzing data you have thrown away or fundamentally altered to store it in a traditional data warehouse. You must retain data in its original form if you want to be an analytically-driven organization.”
– Scott Mutchler, VP of Advanced Analytics at QueBIT

Big Data Solutions Add Value Compared to Traditional Data Warehouses

Traditional data warehouses are the workhorse of reporting and help drive critical business decisions. However, these data warehouses present some significant challenges:

  • Cost of storage ($5/GB vs $0.25/GB with Apache Hadoop)
  • Scalability for data retrieval
  • Limited ability to store unstructured text data
  • Adding data to data warehouses is a slow, laborious process

On the contrary, QueBIT’s big data solutions are a perfect initial storage solution for data in its raw, unprocessed state (often called a data lake). This allows data to be stored quickly. It also preserves the data integrity because it is not aggregated or processed in a predefined way. This makes QueBIT’s big data solutions ideal for analytics where data integrity is of utmost importance.

Additionally, QueBIT’s big data solutions are highly cost-effective with storage costs around $0.25/GB. The solution is also highly scalable, with nearly linear scalability as data sizes increase.

QueBIT’s Technology Stack

QueBIT aims to drive maximum business value while minimizing costs. We do not believe in a one-size fits all solution. Our technology stack includes several options that include low-cost, open source technologies such as:

We also fully support a more user-friendly, commercially-supported, IBM-based technology stack:

Benefits of QueBIT’s Big Data Analytics

  • Preservation of all your corporate data to drive competitive advantages
  • A highly-scalable big data analytics platform that delivers results quickly
  • Cost-effective big data analytics stack on-premise or in the cloud
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