Igniting data discovery: SnapLogic delivers a “quanta” in improvement over Informatica

md_craig-BW-1443725112In my previous blog post, I talked about how a pharmaceutical company uses SnapLogic and Amazon Redshift to capitalize on market and environmental fluctuations, driving sales for its asthma relief medication. In this post, I’ll tell you the path the company took to get there. Hint: It wasn’t a straight one.

An IT organization abandons Informatica

Several months prior to launching its current environment, with data flows powered by SnapLogic, the pharmaceutical company tried, unsuccessfully, to integrate its data warehouses in Redshift using Informatica PowerCenter and Informatica Cloud. The IT team’s original plan was to move data from Salesforce, Veeva, and third-party sources into Amazon Simple Storage Service (S3), and then integrate the data into Redshift for sales and marketing analytics.

However, the project stalled due to difficulty with Informatica PowerCenter, the IT team’s initial choice for data integration. PowerCenter, which Informatica describes as a “metadata-driven integration platform,” is a data extract, transfer, and load (ETL) product rooted in mid-1990s enterprise architecture. The team found PowerCenter complicated to use and slow to deliver the urgently needed integrations.

Looking for faster results, the pharmaceutical company then attempted to use Informatica Cloud, Informatica’s cloud-based integration solution. The data integration initiative was again derailed, this time by the solution’s lack of maturity and functionality. The pharmaceutical company’s data was forced back on-premises, jeopardizing the entire cloud data warehouse initiative.

Data integration aligned with the cloud

But the IT team kept searching for the right data integration solution. “Cloud was instrumental to our plans, and we needed data integration that aligned with where we were headed,” said the senior business capability manager in charge of the integration project. The pharmaceutical company chose the SnapLogic Enterprise Integration Cloud.

After a self-evaluation, the IT team was able to quickly build data integrations with SnapLogic; no specialized resources or consultants were required. To accomplish the integrations in Redshift, the pharmaceutical company used:

  • Salesforce Snap
  • Redshift Snap
  • Various RDBMS Snaps
  • ReST/SOAP Snaps
  • Transformation Snaps

With the data integration accomplished in a matter of days, the IT organization was assured that current skills sets could support the company’s future global BI architecture. In addition, the IT team found the SnapLogic Enterprise Integration Cloud easy enough for business users, such as the marketing team, to integrate new data into Redshift.

Leveraging Redshift’s nearly infinite availability of low-cost data storage and compute resources, the analytic possibilities are equally limitless – igniting the marketing team’s discovery of new strategies to drive new insights, revenues, and operational efficiencies.

SnapLogic delivers a “quanta” in improvement 

What is quanta? It’s the plural of the word “quantum,” a physics term that describes “a discrete quantity of energy proportional in magnitude to the frequency of the radiation it represents.” If you’re not a physicist, your closest association is probably “quantum leap” – basically a gigantic leap forward.

Which is exactly what SnapLogic delivers. With regard to Informatica, Gaurav Dhillon, founder and CEO of SnapLogic, says:

“Fundamentally, I believe that SnapLogic is 10 times better than Informatica. That’s a design goal, and it’s also a necessary and sufficient condition for success. If a startup is going to survive, it’s got to have some 10x factor, some quanta of a value proposition.

“The quanta over the state of the art – the best-of-the-best of the incumbents – is vital. SnapLogic can fluently solve enterprise data problems almost as they are happening. That has a ‘wow’ factor people experience when they harness the power of our data integration technology.”

The SnapLogic Enterprise Integration Cloud is a mature, full-featured Integration Platform-as-a-Service (iPaaS) built in the cloud, for the cloud. Through its visual, automated approach to integration, the SnapLogic Enterprise Integration Cloud uniquely empowers both business and IT users, accelerating cloud data warehouse and analytics initiatives on Redshift and other cloud data warehouses

Unlike on-premises ETL or immature cloud tools, SnapLogic combines ease of use, streaming scalability, on-premises, and cloud integration, and managed connectors. Together, these capabilities present an improvement of up to 10 times over legacy ETL solutions such as Informatica or other “cloud-washed” solutions originally designed for on-premises use, accelerating cloud data warehouse integrations from months to days.

To learn more about how SnapLogic allows citizen data scientists to be productive with Amazon Redshift in days, not months, register for the webcast “Supercharge your Cloud Data Warehouse: 7 ways to achieve 10x improvement in speed and ease of Redshift integration.”

Craig Stewart is Vice President, Product Management at SnapLogic.

Discovery in overdrive: SnapLogic and Amazon Redshift power today’s pharma marketing

md_craig-BW-1443725112At its most fundamental, pharmaceutical marketing is based on straightforward market sizing and analytic baselines:

“The global market is composed of many submarkets [aka therapeutic categories] (TCs), whose number is given and equal to nTC. Each TC has a different number of patients (PatTC) in need of treatment for a specific disease, which determines the potential demand for drugs in each submarket. This number is set at the beginning of each simulation by drawing from a normal distribution [PatTC~N(μp,σp)] truncated in 0 to avoid negative values, and it is known by firms. Patients of each TC are grouped according to their willingness to buy drugs characterised by different qualities.”*

Yet capturing market share in today’s competitive environment is anything but easy. In the recent past, an army of sales reps would market directly to doctors, their efforts loosely coupled with consumer advertising placed across demographically compatible digital and traditional media.

This “spray and pray” approach with promotional spending, while extremely common, made it difficult to pinpoint specific tactics that drove individual product revenues. Projections and sales data factored heavily into the campaign planning stage, and in reports that summarized weekly, monthly, and quarterly results, but the insights gleaned were nearly always backward-looking and without a predictive element.

A pharmaceutical company pinpoints opportunity

Today, sophisticated pharmaceutical marketers have a much firmer grasp of how to use data to drive sales in a predictive manner – by deploying resources with pinpoint precision. A case in point: To maximize the market share of a prescription asthma medication, a leading pharmaceutical company uses SnapLogic and Amazon Redshift to analyze and correlate enormous volumes of data on a daily basis, capitalizing on even the smallest market and environmental fluctuations.

  • Each night, the marketing team takes in pharmacy data from around the US to monitor sales in each region, to learn how many units of the asthma medication sold the previous day. These numbers are processed, analyzed, and reported back to the sales team the following morning, allowing reps to closely monitor progress against their sales objectives.
  • With this data, the pharmaceutical marketing team can monitor, at aggregate and territory levels, the gross impact of many variables including:
    • Consumer advertising campaigns
    • Rep incentive programs
    • News coverage of air quality and asthma
  • However, the pharmaceutical marketing team takes its exploration much deeper. Layered on top of the core sales data, the marketing team correlates weather data from the National Weather Service (NWS) and multiple data sets from the US Environmental Protection Agency (EPA), such as current air quality, historic air quality, and air quality over time. Like the sales data, the weather and EPA data cover the entire US.

By correlating these multiple data sets, the marketing team can extract extraordinary insights that improve tactical decisions and inform longer-term strategy. At a very granular, local level, the team can see:

  • How optimal timing and placement of advertising across digital and traditional media drives demand
  • Which regional weather conditions stimulate the most sales in specific locales
  • The impact of rep incentive programs on sales
  • How news coverage of air quality and asthma influences demand

Ultimately, the pharmaceutical marketing team can identify, with uncanny precision, markets to concentrate spending on local and regional media, which can change on a constant basis. In this way, prospective consumers are targeted with laser-like accuracy, raising their awareness of the pharmaceutical company’s asthma medication at the time they need it most.

The results of the targeted marketing strategy are clear: The pharmaceutical company has enjoyed significant market share growth with its asthma relief medication, while reducing advertising costs due to more effective targeting.

Tools to empower business users

The pharmaceutical industry example exemplifies perhaps the biggest trend in recent business history: massive demand for massive amounts of data, to provide insight and drive informed decision-making. But five years after data scientist was named “the sexiest job of the 21st century,” it’s not data scientists who are gathering, correlating, and analyzing all this data; at the most advanced companies, it’s business users. At the pharmaceutical company and countless others like it, the analytics explosion is ignited by “citizen data scientists” using SnapLogic and Redshift.

In my next blog post, the second of this two-part series, I’ll talk about how SnapLogic turned around a failing initial integration effort at the pharmaceutical company, replacing Informatica PowerCenter and Informatica Cloud.

To find out more on how to use SnapLogic with Amazon Redshift to ignite discovery within your organization, register for the webcast “Supercharge your Cloud Data Warehouse: 7 ways to achieve 10x improvement in speed and ease of Redshift integration.”

Craig Stewart is Vice President, Product Management at SnapLogic.

* JASSS, A Simulation Model of the Evolution of the Pharmaceutical Industry: A History-Friendly Model, October 2013

July 2016 Snap Update

snaplogic_snapsThis weekend is our July 2016 Snap release. We have added new Tableau 9 Snaps that support the 9.1 version of Tableau. New Snaps include: REST, Write, and TDE Formatter.

Below is a list of all of the updated Snaps in this release: Continue reading “July 2016 Snap Update”

Eight Data Management Requirements for the Enterprise Data Lake

SnapLogicDataLakeMgmt01itbe_logoThis article originally appeared as a slide slow on ITBusinessEdge: Data Lakes – 8 Data Management Requirements.

2016 is the year of the data lake. It will surround, and in some cases drown the data warehouse and we’ll see significant technology innovations, methodologies and reference architectures that turn the promise of broader data access and big data insights into a reality. But big data solutions must mature and go beyond the role of being primarily developer tools for highly skilled programmers. The enterprise data lake will allow organizations to track, manage and leverage data they’ve never had access to in the past. New data management strategies are already leading to more predictive and prescriptive analytics that are driving improved customer service experiences, cost savings and an overall competitive advantage when there is the right alignment with key business initiatives. Continue reading “Eight Data Management Requirements for the Enterprise Data Lake”

March 2016 Snap Update

This weekend is our latest SnapLogic Snap Update, with many new and updated Snaps being delivered. Here’s a brief overview. Be sure to contact our Customer Success team if you have any questions about the release.

There is a new RabbitMQ Snap Pack available with this update, which contains a Consumer and Producer Snap. Updated Snap Packs include: Continue reading “March 2016 Snap Update”

REST GET and the SnapLogic Public APIs for Pipeline Executions

As a part of a wider analytics project I’m working on, analyzing runtime information from the SnapLogic platform, I chose to use the functionality exposed to all customers, the Public API for Pipeline Monitoring API and the REST API. These two things are combined in this post. I started by reading the documentation (of course), which shows the format of the request and response. So I created a new pipeline and dropped a REST GET Snap on the canvas:

snaplogic_REST_pipeline
Continue reading “REST GET and the SnapLogic Public APIs for Pipeline Executions”