Big Data Analysis

Everywhere you look, you see data — and lots of it. For a large enterprise, big data may be in the petabytes or more, while for a small or mid-size enterprise, data volumes that grow into tens or hundreds of terabytes can become challenging to analyze and manage. Organizations are storing a variety of unstructured data from websites, infrastructure logs and sensors, and ecommerce velocity gives less and less time to interpret and act on information.

If it’s hard to comprehend a few thousand rows of numbers, what chance do you have to get insight from millions or billions of rows at a time? How do you get value from all that data?

The proliferation of data makes easy-to-use business analysis tools more important than ever. The ability for business users to visualize data so they can spot trends and outliers is not nice to have, it’s critical. Otherwise you’ve got warehouses of data but no data intelligence.

In Memory or Connect Live
Options for fast in-memory data engine or live database connection

Tableau has optimized direct connections for many high-performance databases, cubes, Hadoop, and cloud data sources such as Salesforce.com and Google Analytics. You can work directly with your data to create reports and dashboards. Tableau lets you connect live or bring your data into its fast, in-memory analytical engine.

It’s easy to get started: just connect to one or more than 30 databases and formats supported by Tableau, enter your credentials and begin, with a single click to select live connect or in-memory analytics. You can publish web dashboards with live connections on your corporate portal, SharePoint or wiki so your data automatically refreshes. Mix-and-match multiple data sources from different database types in the same web dashboard.

Tableau's in-memory data engine is not subject to the restrictions of many in-memory solutions which require that all your data fit into your machine's RAM. Advanced in-memory technology takes advantage of all the memory on your laptop or PC, down to the hard disk, so your analysis can be wicked fast and huge, all at the same time.

Self-Reliant Analysis
Get value from data with Tableau's big data BI

Tableau's powerful big data software enables the people who know the data the best to do their own analysis. With drag & drop, point & click ease to build charts, reports and dashboards, Tableau gets people throughout an organization connected directly to their data. There’s no more waiting in an IT queue to answer questions, so now you can begin getting answers from your data.

This dashboard uses millions of rows of stock data to show trends in key securities. It was built without any programming by a regular business user. With the right tools, anyone who needs answers from data can get them.

Using Tableau for self-reliant visual analytics means you can analyze data with lightning-fast queries on massive amounts of data. By giving you this ability to ask – and answer – questions at the speed-of-thought, Tableau's big data software puts you at a distinct advantage.

Big Data Trends
It's hard to find an organization or industry that has less data now than 10 or 20 years ago.

We’ve entered the era of the “industrial revolution of data”, with the equivalent of “data factories”, as noted by Joe Hellerstein at UC Berkeley.

Almost every web page view worldwide generates log information that is aggregated, shared and analyzed. Sensors are extending from building heating and air conditioning to autos and motion detection in gaming.

While per-petabyte storage costs continue to fall and there are a whole host of database options to store unstructured or semi-structured data, “… the complimentary scarce factor is the ability to understand that data and extract value from it”, as noted by Google Chief Economist Hal Varian in McKinsey Quarterly.

Thankfully, with Tableau anyone can see and understand big data. In this dashboard, see a heat map of big data opportunities by industry, the growing popularity of the term “big data” on Google Search, and maturity levels for an organization’s analytical innovation.