Just how much data is big data? What does cloud computing really mean? How is this different than SQL? Oracle? Can you do analytics? A whirlwind of questions can be asked of many “big data” companies. Companies that help others manage large volumes of data have long had trouble describing what they truly are. This is partly because the range of solutions offered is immense. These solutions fall into two main categories.

First, data warehousing companies help companies deal with data overload. The companies may have recognized they wanted to keep their data, but couldn’t manage it themselves. They choose to buy hardware or occasionally a cloud offering to collect and maintain historical data. This offering often allows for simple analytical queries like indexing and basic aggregations. However, they lack analytic power, and either need to do pre-aggregating and indexing before each complex query or split the data set into smaller segments for analysis.

Second, there are analytic offerings. These include Excel, and for the more technical, SQL. While Excel is very flexible, it is hampered by its inability to work on large data sets and relative lack of power. SQL has relatively strong analytic capabilities, but forces data to be stored relationally. This makes the data take up much more space than it needs to, and makes many types of queries, especially time series, very sluggish on large data sets.

Companies are struggling to use these solutions to solve their problems. It’s important to consider that the biggest concern of most customers is how to leverage data to drive business decisions. The proper solution tackles this problem by providing robust analytic flexibility and power enabling both technical and non-technical decisions makers to drive strategic vision and change. This requires an incredibly fast big data platform that combines the flexibility and simplicity of Excel with the ability to do even more powerful analytics than SQL.

To truly meet our customers’ goals we have created a Big Data Analytics Platform (BigDap). We can take all the data any customer could throw at us (big data), and empower users to do lightning-fast and powerful analyses that drive business results (analytics). Perhaps most importantly, we offer non-technical end users a flexible spreadsheet like, web browser interface as intuitive as Excel, and technical users an incredibly powerful XML based query language accessible via several programmatic interfaces such as APIs, ODBC, MS Excel Add-in, and an SDK that supports most modern programming languages, all delivered securely via a managed cloud. (platform).

Using the managed cloud means that users can access the data and analytic power securely from any web browser. This ensures that there is exactly one version of the truth, and everyone working together will see the same data at the same time. It also reduces hardware costs and lets the company focus on their business needs, not how to store data.

BigDap is more than just a way to manage your data. It is more than an on demand tool to analyze some of it. This is a Big Data Analytics Platform: let your data lead the way!

E-Commerce Times had a nice story about 9 Ways to Sharpen Business Intelligence.  David Carr writes:

In a time of economic turmoil, business intelligence (BI) initiatives stand out for their potential to improve corporate performance… Compared with many enterprise IT projects, BI requires relatively modest investments… [which can] pay off the most for organizations that are serious about doing it right…

He goes on to list 9 ways to maximize BI investments (please visit the link to read the details of each):

1. Customize user interfaces/dashboards for specific roles
2. Integrate data across departments and applications
3. Foster a culture of data-driven decision making
4. Implement processes for continuous data quality improvement
5. Demonstrate improved planning, operations and other outcomes
6. Implement a formal KPI methodology (e.g., Balanced Scorecard, Six Sigma, etc)
7. Deploy alerts/notifications
8. Implement employee training
9. Improve analytics capabilities.

In addition to data warehousing, 1010data lets IT professionals build customizable UIs that provide simple and advanced reporting and querying capabilities; this directly addresses the need in the first point for roles-based UIs and dashboards.

Regarding the second point, Carr explains the problems of having data silos and disparate tools.  We have found that providing analytics and data warehousing capabilities as a service makes it easier to offer clients an enterprise-wide system with a common interface and a unified store of data (which helps them to arrive at “a single version of the truth,” as we like to say).

He also talks about challenges inherent in extracting and rolling up data, and about data quality issues; our clients appreciate that the 1010data platform works directly on raw data, so there is no need for extensive data pre-processing, grooming, aggregation, etc.  This helps accelerate “time-to-insight.”

Finally, in reference to the last point, please see our post A Modest Proposal Regarding Advanced Analytics; also take a look at the news we announced: 1010data Advances Hosted Analytics and Reporting.