The data management provider has announced its new Marketing Data Lake, which it describes as the first such repository specifically for the needs of marketers.

As Informatica explains in a recent e-book on the subject, a data lake is “a data repository that lets you store and process all your data, from multiple sources, in its native format without having to pre-structure it.”

It complements data warehouses, the company notes, in that generates data schemas “on read,” or when the data is exported and used, instead of “schema-on-write” when it goes into the repository, as with warehouses. A schema is a blueprint for data organization.

Salesforce strengthened its big data offering last week, announcing partnerships with powerhouses including Google, Cloudera, Hortonworks, New Relic, Informatica and Trifacta. Data preparation providers Informatica and Trifacta also joined the fold, charged with helping translate big data into a form digestible by business executives.

The move makes Salesforce Wave a front-end solution to help businesses slice and dice the extensive data reserves held both by its partners and its clients.

Salesforce launched the Wave data service late last year to help businesses extract actionable data from growing pools of recorded clicks and digital interactions. The new partnerships increase the amount of data its clients can access, and also give them access to the analytical capabilities of those partners.

Dark marketing clouds ahead? Let us help you see clearly. Contact us.

Digest...

DON'T let fear or uncertainty stop you from starting today.

DO learn the languages of analytics.

DO combine your data with other data sets. DON'T think you can do it alone.

DON'T expect the data to tell you everything you need to know about your customers. DO augment your data-driven insights via other types of intelligence such as qualitative and/or contextual research.

DO tear down the walls to collaborate.

DON'T forget it's a work in progress.

DO be flexible.

DON'T use the past to hold back future decisions.

DO make data your friend not your enemy.

► Receive a FREE daily summary of The Marketing Technology Alert ◄          

At this year's conference, DMA2014, a survey of 584 attendees by Infogroup found the number reaping rewards has risen significantly, now standing at almost half (49%).
However, the survey also highlighted that marketers continue to struggle with analysis of the huge amounts of data now available to them. For 21%, analysis is their biggest concern moving forward into 2015, followed by data implementation (16%) and collecting data (15%). More than half of marketers surveyed said they do not collect enough data while 10% said they collect too much. Of those who collect too much data 25% believe collecting data remains their biggest challenge.

► Receive a FREE daily summary of The Marketing Technology Alert ◄

1. One third of all data will be stored in or will pass through the cloud by 2020. (Chassis Plans)

2. Dirty data, or poor data quality, costs U.S. businesses $600 billion annually. (Fathom)

3. Eighty-three percent of companies have started some sort of Big Data program, although many remain in fledging stages—especially small businesses that have fewer resources to invest. (Experian Data Quality)

4. San Francisco is ranked the number one U.S. city in open data innovation, followed by New York and Boston. (U.S. City Open Data Census)

5. On average, companies collect customer and prospect data from 3.4 channels. The most common channel for interacting with customers is a company's website, followed by the sales team and then the call center. (Experian Data Quality)

6. There are nearly as many pieces of digital information as there are stars in the universe. (Realcomm)

7. Seventy-nine percent of companies have an analytics team. The median number of employees on an analytics team is 22. (Experian Data Quality)

8. By 2018 the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills to fill data-centric jobs. (McKinsey Global Institute)

9. In 2000, just one quarter of the world's stored information was digital. Today, more than 98% of all stored information is digital. (Foreign Affairs)

10. Brands and organizations receive 34,722 Facebook Likes every minute. (Big Data Insight Group)

11. An estimated 80 to 90% of the data in any organization is unstructured—or doesn't fit neatly in a traditional row-column database. Some examples include email messages, word processing documents, videos, photos, audio files, presentations, and Web pages. (Webopedia)

12. The Big Data market will reach $16.9 billion by 2015, up from $3.2 billion in 2010. (International Data Corporation)

Instead, develop the skills on your team.

Digest...

Based purely on the data, a really good data scientist will probably tell you the odds are poor that you’ll be able to find and hire really good data scientists. Surveys say there simply aren’t enough people with the unusual blend of software skills and statistical savvy to go around. Arguably even more important, high-impact data scientists bring collaborative temperaments and business acumen to data-driven initiatives. Unfortunately, there’s no shortage of individuals with just enough statistical and software knowledge to be data-dangerous. For many organizations, a mediocre data scientist may be worse than none at all.

The smartest thing I’ve seen organizations start doing is seed-fund and empower small cross-functional data-oriented teams explicitly charged with delivering tangible and measurable data-driven benefits in relatively short periods of time. The accent is on the word team; the emphasis is on building greater data capability than better digital infrastructures. The goal is to make all of the organization — not just the geeks and quants — more conversant in how to align probability, statistics, technology and business value creation. No black boxes or centers of analytic excellence here; they want data science to be a cultural value, not just a functional expertise.

Without exception, every team I ran across or worked with hired outside expertise. They knew when a technical challenge and/or statistical technique was beyond the capability. But, unsurprisingly, the outside advisors — in one case, an academic, in others, quants from digital consultancies — were better able to collaborate with teams that had really tried to get their minds around a design challenge. The relationship was less of an RFP box-ticking exercise than a shared space for experimental design.

__________________

► Receive a FREE daily summary of The Marketing Technology Alert directly to your inbox. To subscribe, please go to http://ineomarketing.com/About_The_MAR_Sub.html  (your privacy is protected).

Advanced/ Condensed...

To exploit the business opportunity hiding in big piles of data - marketers must understand that data is increasingly:

1. Diverse, making integration costly and complex. Look at the data pouring out of smart devices, wearable computers, sensors, social media, video, etc. and it’s easy to believe that 90% of all data has been created during the past 2 years (according to the US Chamber of Commerce and Norway’s SINTEF ITC.)
2. Large, challenging your technology and analytics ability.  
3. Messy, challenging your firm’s obsession with using only high quality, curated data for analysis.
4. Not owned or controlled by you (at least a good chunk of it is this way), challenging the natural tendency to hoard data in silos and shy away from data sharing.

For B2B marketing executives, the best place to start their Big Data journey is by focusing on their buyers' journeys and by doing something that may seem a little counterintuitive: Start by understanding your best customers and work backwards through their journey to identify the patterns that led them to be successful and to stand out from the rest. 

____________________________________________________

► Receive a FREE daily summary of The Marketing Technology Alert directly to your inbox. To subscribe, please go to http://ineomarketing.com/About_The_MAR_Sub.html  (your privacy is protected).