Strata Data Conference London 2018
21-24 May, 2018
Let's talk about faster insights for your business users at Booth #K209
Join us from 21 - 24 May at Strata Data Conference London, to tap into the minds of expert speakers from around the world and network with thousands of data scientists, engineers, analysts and business managers.
Whether you are ready to kick off a visual analytics project or have technical questions for our engineers, we'd love to talk to you.
Swing by Booth #K209 or request a meeting in advance.
Strata London 2018 Highlights:
- Real-Time Trade Surveillance Is Not Just about Trade Data with Paul Lashmet | Tuesday, 22 May | 9:05 AM | Location: Capital Suite 4
- A Tale of Two BI Standards: Data Warehouses and Data Lakes with Randy Lea | Wednesday, 23 May | 2:05 PM | Location: Capital Suite 2/3
- Executive Briefing: BI on Big Data with Mark Madsen & Shant Hovsepian | Wednesday, 23 May | 4:35 PM | Location: Capital Suite 17
- Fill out this Eckerson Survey for a free t-shirt - Bring a print out of your landing page to claim your prize
Can’t make it to Strata this time? Download Arcadia Instant and maybe you’ll be speaking on behalf of Arcadia Data at Strata next year!
Real-Time Trade Surveillance is Not Just About Trade Data
& Advisor for Financial Services
Tuesday, 22 May | 9:05 AM
Location: Capital Suite 4
To find instances of illegal trade practices you must think beyond traditional data sources.
Consider the vast amounts of data analyzed, the variety of sources, the high frequency of trades, the complexity of cross-border transactions, and the overlapping layers of client relationships. All of these elements need to be connected and correlated to identify both the trading activities and the intent of the traders.
Paul Lashmet explains how alternative data sources enhance trade surveillance by providing a deeper understanding of the intent of trade activities.
Join this speaking session to learn how to kickstart your use of alternative data as a compliance asset through practical examples that have been employed by your peers in the industry.
A Tale of Two BI Standards: Data Warehouses and Data Lakes
Chief Revenue Officer
Wednesday, 23 May | 2:05 PM
Location: Capital Suite 2/3
Data lakes as part of the logical data warehouse (LDW) have entered the trough of disillusionment. Some failures are due to lack of value from businesses focusing on the big “data” challenges and not the big “analytics” opportunity. Data is just data until you analyze it.
While the data management aspect has been fairly well understood over the years, the success of business intelligence (BI) and analytics on data lakes lags behind. In fact, data lakes often fail because they are only accessible by highly-skilled data scientists and not by business users. But BI tools have been able to access data warehouses for years, so what gives?
In this talk, we’ll discuss:
- Why existing BI tools are architected well for data warehouses, but not data lakes.
- The pros and cons of each architecture.
- Why every organization should have two BI standards: one for data warehouses and one for data lakes.
Executive Briefing: BI on Big Data
CTO & Co-Founder
Wednesday, 23 May | 4:35 PM
Location: Capital Suite 17
If your goal is to provide data to an analyst rather than a data scientist, what’s the best way to deliver analytics? There are 70+ BI tools in the market and a dozen or more SQL- or OLAP-on-Hadoop open source projects.
A panel of experts details the trade-offs between a number of architectures that provide self-service access to data, and industry researcher Mark Madsen discusses the pros and cons of architectures, deployment strategies, and customer examples of BI on big data.
- Traditional BI platforms based on semantic layers and SQL/MDX generation
- Server and desktop BI tools based on direct mapping of data
- Distributed BI platforms (e.g., MPP and data native)
- OLAP- and SQL-on-Hadoop engines
Ask Me Anything: Architecting a Data Platform for Enterprise Use
CTO & Co-Founder
Thursday, 24 May | 12:05 PM
Location: Capital Suite 14
Join Mark Madsen and Shant Hovsepian to discuss analytics strategy and planning, data architecture, data management, and BI on big data.