4 Problems with Big Data (And How to Solve Them)

Big Data Innovation Summit returns to Boston, Sep 9-10, with 60+ sessions covering Big Data biggest problems (and how to solve them). Use code KD300 to save $300 off all two-day pass prices.

Big Data Innovation Summit, Boston, Sep 9-10, 2015 Managing large datasets can be problematic. Compared to smaller amounts of data, analysis, storage, privacy and interpretation can cause difficulties for today's data leaders.

Rest assured, the Big Data Innovation Summit returns to Boston next month, on September 9-10, with 60+ sessions covering Big Data's biggest problems (and how to solve them!) Use discount code KD300 and save $300 off all two-day pass prices.

Check out the schedule here:

If you are interested in attending or have any questions please contact Hayley Law at hlaw@theiegroup.com (+1 415 692 5378) quoting your discount code, or you can confirm your discounted pass here: bit.ly/1L1eysV

1) Where should I store it?

The more data an organization has, the more complex the problems of managing it can become. Our Cloud & Data Architecture and Apache Innovation tracks will explore all your possible storage options, with speakers from Bank of America-Merrill Lynch, StubHub, MapQuest & more...

2) Can I keep it secure?

Five of the six most damaging data thefts of all time have happened in the last two years. At the same time, failing to comply with data protection laws can lead to expensive lawsuits. Data security and privacy policies are simply too important to ignore. Hear how Timothy Persons, Chief Scientist at the US Government Accountability Office is protecting America's data.

3) False Positives

It is very difficult to draw useful insights from Big Data without a solid analytics model in place. With Big Data, sometimes 'thinking fast' can lead to false positives. Jack Levis, Director of Process Management at UPS will share how the organization is 'Problem Solving Through Analytics' and how you can do the same.

4) Incorrect Findings

Big Data can guide you to a more accurate prediction of the future, but it should not be taken at face value; there needs to be a human element involved to process, analyze and find conclusions. Hear how the Boston Red Sox has transformed into a data-driven organization that goes beyond on-field analytics.

For an idea of what to expect, check out this presentation from Riley Newman, Head of Data Science at Airbnb 'A/B Testing in the Real World'.

We hope to see you next month!

Big Data Innovation Team