Alteryx Inspire 2016: Is There a Cure for Data Hate?

Alteryx Inspire 2016: Is There a Cure for Data Hate?

Returning from Inspire 2016 –the annual user conference from Alteryx – as I write this, I can’t get away from one burning question rattling around my brain: Why do people hate their data so much? Before delving into that one, let’s provide a little background here. Alteryx likes to distinguish itself as a “platform” –as opposed to a point solution – for self-service data analytics. Including capabilities for data blending (some have called it integration), data preparation, enrichment, and predictive/advanced analytics, the solution is geared primarily toward data scientists and business analysts, especially those that deftly balance a modicum of technical acumen with a healthy dose of business expertise. Accordingly, the Inspire conference is chock full of folks whose primary job function involves extracting meaningful insight from data, a task monumentally easier said than done. Through casual conversations, and after listening to several “before and after” style customer accounts, a common thread that emerged was a deep dissatisfaction with the raw material used to create insight. So, why do people hate their data? There are several reasons (in no particular order): It’s gross. Riddled with corrupted, duplicated, incorrect, or absent fields, the typical data source has major quality issues. To make matters worse, these issues arise regardless of data source, be it an application, an operational data store, a data warehouse, or just a spreadsheet. You need the Keymaster of Gozer just to find it. In the heat of analysis, with all the brain-burning and number-crunching, how often does someone need data that isn’t immediately at their fingertips? All. The. Bleeping. Time. For many of these poor souls, adding a field to a data set, or, God forbid,...
Three Key Criteria When Selecting Data Visualization Tools

Three Key Criteria When Selecting Data Visualization Tools

So how many rows of data did you say this tool can ingest? It’s backed by a massively parallel processing engine? It runs in-memory? And…why should I care about any of this? If flexibility, firepower, and adaptability were the only considerations for technology implementation, these decisions would be easier. The fickle business user community, though, needs more convincing than raw numbers on paper. When it comes to tools like interactive visualization, for those that survive or thrive based on business user adoption, connecting with a broader community is absolutely vital. Recent Aberdeen research explored the impact of data visualization and found that, in addition to greater analytical engagement, these users shared three common characteristics of satisfaction. 1: Ease-of-use Interactive visualization is all about exploring the data behind the data — the “why?” behind what is presented. All too often though, the tools don’t resonate with the business users typically asking those questions. Ease-of-use can be difficult to describe, and varies from company to company, but the general concepts apply broadly. Users need intuitive, drag-and-drop, easy drill-down capabilities in order to explore the data. 2: Data connectivity Nothing kills the momentum of analytical activity like hitting the invisible wall of data absence. In the heat of an analysis, users need the ability to pull in data from sources not necessarily presented to them in the original dashboard or visualization. The ability to connect to, and ingest information from, other sources is a key enabling factor of interactive visualization. 3: Line-of-business fit Closely tied to ease-of-use, users need tools that fit the logic and taxonomy of their business area. Sometimes that involves...
Can Your Business Intelligence & Analytics Truly Adapt? [Webinar]

Can Your Business Intelligence & Analytics Truly Adapt? [Webinar]

We’ve talked before about how managing Big Data in the enterprise is a double-edged sword — there’s a lot of it coming into the business at a breakneck pace, but moreover, it’s more complex than ever. Add to this the fact that many organizations lack real-time insight into customer needs and behavior, and that data-savvy employees of these companies can’t easily access data and analytical insight when they need it most. This isn’t a surprise, really — traditional on-premise business intelligence (BI) platforms, although effective at creating static views of historical information, fall far short when it comes to flexibility and speed. So the questions really become for companies: How can I transform Big Data into “Fast Data” and hasten the decision process, so I can better serve my customers? Is my BI platform adaptable enough right now to even make this a reality? To expand upon the solution to this customer service problem plaguing many enterprises, Aberdeen Group VP and Principal Analyst Michael Lock will discuss findings from his latest research in a live webinar on Thursday, June 9th, at 1 PM EDT. In the session entitled “Building an Adaptive Approach to Business Intelligence and Analytics,” you’ll learn: What business pressures drive the need for new approaches to BI Key practices that empower the analytical workforce Top strategies for understanding and meeting the needs of today’s customers Be sure to register for the live webinar at 1 PM EDT on Thursday, June 9th. Even if you can’t make this time, be sure to register anyways — we’ll send you a link to the on-demand recording...
Stat of the Week: Fast Data Through Cloud Analytics

Stat of the Week: Fast Data Through Cloud Analytics

Any business knows the drill — there’s more data than ever before, complex as ever, coming in faster than ever before. But cloud-based analytics in particular has become a tool to empower a wide variety of business users with faster access to relevant data, as this Stat of the Week shows. Be sure to also check out the related content brief, Unleashing the Power of Analytics in the...
What’s Cloud Got to Do with It? (When it Comes to Analytics) [WEBINAR]

What’s Cloud Got to Do with It? (When it Comes to Analytics) [WEBINAR]

I’ll try not to break into a Tina Tuner song and dance while delivering the answer (I don’t think anyone deserves the pain that would ensue from this), but the answer to this title question is…a lot. While the analytical capabilities available today are more diverse (e.g. the Internet of Things, geospatial, predictive analytics), the cloud has not lost a step in its ability to house these capabilities. Additionally, as more applications and data sources migrate to a cloud environment, cloud-based analytical solutions are becoming more and more relevant as a way to bridge the gap between data, and create relevant insights derived from all over the organization. Oh, and never fear — capabilities like managed reporting and static dashboards work just as well in the cloud as they do on-premise. So what’s the takeaway from all of this? Top-performing companies realize these cloud benefits, and are expanding their on-premise analytical activities into cloud environments to reduce reliance on IT, improve analytical adoption and engagement, and produce repeatable business results.` Live Webinar For more information on  the subject, join us at 1pm EST on Tuesday, April 26, 2016, for the live webinar, The Intelligent Cloud: Self-Service Insight Drives Business Execution, where Aberdeen V.P. and Principal Analyst Michael Lock will discuss key research findings, including: Top pressures driving the need for cloud-based analytics Best-in-Class strategies for data management and visualization Business impact of efficient analytics in a cloud environment During the event, you’ll also have a chance to share your questions. So come prepared for a live Q&A as well! And we know you’re busy: If the time doesn’t work for your schedule, consider registering for the webinar...
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