9 Key Takeaways About Cloud and Analytics from Data Summit 2017

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Data Summit 2017, an annual conference presented by Big Data Quarterly and Database Trends and Applications, was recently held in NYC. The event drew industry leaders who spoke about the changing world of data management and the implications for technology, people, and processes. New big data technologies, cloud, and analytics were among the key areas scrutinized in educational presentations, keynotes, and hands-on workshops.

Here are nine key takeaways about cloud and analytics from the experts. 

1-The forecast is clouds: While Amazon is the dominant player in the cloud market today, don’t count anyone out just yet. Anything can change and cloud providers are competing fiercely — similar to mobile phone services providers — and taking customers from each other. Oracle is targeting Microsoft as much as it is targeting Amazon. Amazon and Azure are the current public cloud leaders, but a price war could shake up the future. Almost 70% of the market is owned by Amazon and Microsoft. Azure doubles each year, up 93% in 2016, but during the Amazon S3 outage in early 2017, it wasn’t Azure or Oracle that benefited, but Google, which increased its business over 12% in just 2 days. — Kellyn Pot'Vin-Gorman, technical intelligence manager for the Office of CTO, Delphix

2-The new world of multiple clouds: Moving from cloud to cloud becomes easier if you standardize on a database that you can use in multiple clouds. — Aerospike CTO and co-founder Brian Bulkowski

3-Data is the new oil: Data is now a kind of capital, on par with financial and human capital for creating new products and services.  — Paul Sonderegger, data strategist at Oracle

4-There are three steps to building a data lake: First, create a “data pond” with raw data copied from existing internal data stores and outside data sources. Once use cases have been defined, the “data lake” can be created with raw and defined data from other systems into a centralized cluster. And last, a “data reservoir” can be created using raw and defined data which is governed and audited to ensure compliance and security. Each of these steps has its own challenges, but it is critical to start with a pond before moving on. — Jonathan Gray, CEO and founder of Cask 

5-Moving to a data-driven culture: Creating a data-driven architecture is easy. Figuring out how to deal with people who are worried that their jobs are in jeopardy or that they will not be able to learn what they need to survive is not easy. A process is required today to help them through it. This is why, the newest position at the organizational leadership level is the emerging role of chief data officer who is responsible for changing the company from being conventional wisdom-driven to being analytics-driven. — Joe Caserta, president of Caserta Concepts

6-More data is not the answer: Doing more with all that data is critical, and power in society will be related to creating value with data. The hero of the age we are entering will be the person who effectively masters data. — Futurist, educator, and author Thornton A. May

7-Data socialization supports self-service analytics: Self-service analytics has many benefits, but it’s also caused the data landscape within many companies to become like the Wild West. The secret to better data and analytics outcomes is “data socialization,” a new approach that integrates traditional self-service data preparation benefits with key attributes common to social media platforms, enabling data scientists, business analysts, and even novice business users to search for, share, and reuse prepared, managed data to achieve true enterprise collaboration and agility. — Jon Pilkington, chief products officer at Datawatch

8-The impact of data science: The top use cases for data science and machine learning now include healthcare – for patient diagnoses, finance – for fraud detection, manufacturing – for anomaly detection, retail – for inventory optimization, insurance – for risk scoring, transportation – for demand forecasts, network – for intrusion detection, e-commerce – for recommendations, and marketing – for customer segmentation. — Rob Thomas, general manager of IBM Analytics

9-Delivering secure BI in the age of Hadoop:  Enterprises shouldn’t have just one BI front end. Sometimes, it takes “a village” to glean insights from data. Companies should make sure to institute standard definitions within their organization. Queries need to be fast and reliable and companies need to determine static security policies. — Josh Klahr, vice president of AtScale

 Many conference presentations have been made available by speakers at www.dbta.com/datasummit/2017/presentations.aspx.    



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