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Big Data

Why You Should Already Have a Data Governance Strategy

October 21, 2016 by Eran Levy

Garbage in, garbage out. This motto has been true ever since punched cards and teletype terminals. Today’s sophisticated IT systems depend just as much on good quality data to bring value to their users, whether in accounting, production, or business intelligence. However, data doesn’t automatically format itself properly, any more than...[read more]

Is that White Smoke Coming from your CRM System?

October 20, 2016 by Gayle Nixon

It's there every time I get in my car, nagging me. There's this little wrench icon, which began to appear about a month ago. And there's the service notification in the middle of my dashboard, with the mileage indicator (-891) telling me that I should have changed my oil almost 900 miles ago. But I haven't had the time. And scheduling a...[read more]


Why It's Time To Get Smart About Recovery

October 20, 2016 by Livia Alexandra

Analytics is all the hype these days, and for good reason. Taking the power of analytics and applying it to the backup and recovery process will be a boon for the IT industry. Analytics will help deal with the data hoarding epidemic and ensure critical data is backed up, without financing storage space and data management for all those pictures of your aunt's cats.[read more]


The True Vision of Big Data in Healthcare

October 19, 2016 by Jared Jaureguy

From the impact of wearable technology to the potential for boosting cancer research, there’s been a lot of buzz about big data in the healthcare space. However, the true vision of big data in healthcare lies not in individual data collection or disparate applications, but in the potential of combining healthcare data to create new...[read more]


How Big Data is Aiding in Disaster Relief

October 19, 2016 by Ryan Ayers

When it comes to disaster preparedness, predicting disasters is one of the biggest problems governments have. That is where big data technology and predictive analytics step in and provide the solution. Over recent years, big data has been able to help scientists and disaster aid agencies narrow down to the hardest hit areas.[read more]

Oracle Goes All In On Cloud

October 18, 2016 by Dave Menninger

I recently attended Oracle OpenWorld for the first time in several years. The message at this year’s event was clear: Oracle is all in on the cloud. I had heard the message, but I didn’t get the full impact until I arrived at the Moscone Center in San Francisco. All signage at the event contained the word “cloud,” and Oracle issued 18...[read more]


The Benefits of Semantic-Based Data Modeling in the Smart Data Lake Era

October 18, 2016 by Sean Martin

The driving force behind enterprise data analytics today is obtaining valuable insights more quickly from large, diverse data sets. A key issue blocking easier access for data scientists, business analysts and IT has been finding an alternative to the current data modeling process.[read more]


Predictive Analytics: The Dos and Don'ts

October 17, 2016 by Rado Kotorov

For organizations looking to make the most out of their relationships and processes, the discovery of meaningful information via analysis can often prove valuable and lead to substantial insight. Data that reveals facts about customers, for example—such as identifying customers who cancel accounts and leave for the competition, those in...[read more]

The New Mainstream Appeal of Apache Spark

October 13, 2016 by Rick Delgado

It wasn’t too long ago that big data was thought of as a niche concept, something reserved for only those companies that were especially tech-savvy. Fast forward a few years and the popularity of big data has increased tremendously, with businesses of all shapes and sizes using it. Such is the way with most technologies, and Apache Spark...[read more]

Demystifying Data Warehouses, Data Lakes and Data Marts

October 12, 2016 by Eran Levy

As data and analytics become a more integral part of business processes in an organization, so the non-DBAs among us might start to feel lost in a sea of technical terms which are frequently thrown around by technical teams.[read more]


Managing Data Tasks with Robotic Process Automation

October 10, 2016 by Rehan Sheikh

Analysts predict that by 2020, Robotic Process Automation solutions will see a compounded annual growth rate of 60.5 percent. Employers are increasingly looking to robotic software to automate many of the data tasks currently completed by humans, for clear reasons, but the process isn’t as cut-and-dry as it first appears.To understand...[read more]

A Shortcut Guide to Machine Learning and AI in The Enterprise

October 10, 2016 by Timo Elliott

Predictive analytics / machine learning / artificial intelligence is a hot topic – what it’s about?Using algorithms to help make better decisions has been the “next big thing in analytics” for over 25 years. It has been used in key areas such as fraud the entire time. But it’s now become a full-throated...[read more]

Any Colo(u)r You Like…

October 7, 2016 by Mark Bradbourne

After Matt Francis’ “50 Shades of Data” at #Data15 I really got to thinking about color, it’s usage and the planning of pallets. So I thought that I would share some of the tools that I use for testing, planning and plotting color for use in Tableau.One of my absolute favorite tools for selecting color pallets is Paletton. Paletton...[read more]


Using Big Data to Optimize Your Media Buying Campaign

October 7, 2016 by Sean Mallon

There are endless numbers of advertising mediums to grow your brand over the Internet. Many companies rely on Google Adwords and Facebook advertising, but there are other strategies worth exploring. Media buying is one of them.Media buying is the purchasing of advertisements from media companies. Over the Internet, it more specifically...[read more]

3 Harsh Truths about Big Data

October 6, 2016 by Eran Levy

Takeaways from Strata NYCWith this year’s Strata + Hadoop World conference in New York over, and after recovering from a hectic week of live demos, presentations and introducing Sisense to anyone who had half a mind to listen, I wanted to take a moment to look back at the event and mostly – how it reflects on the current big data...[read more]