post

The Truth Finds A Way

One trend that continues to gain momentum in the BI world is self service business intelligence, and it has IT groups concerned that the whole focus of a BI team is to champion a single version of the truth. MicroStrategy just released it’s desktop application for free, and version 10.6 is now available. If you have not taken a look at it, it is worth spending some time on. Tableau has built virtually it’s entire business model on self service BI. Any department that can’t get enough resources from the BI team can go and build their own dashboards now. Qlik is the same way. Now Microsoft’s Power BI has stepped into the ring with a growing offering. Alteryx, Sisense, Birst, Zoho – all of these are pouring resources into self service BI. IT groups are running scared, and maybe rightly so. Self service BI doesn’t have to have any training, any experience, any skill sets, any data governance, any single vision of what the single version of the truth is supposed to look like. Power to the people. Democratizing data like never before. Gartner is even saying that this is going to be the death of BI.

ms-excel

Or is it? People have always gone outside of the BI or the IT teams to build reports and analysis. It’s called Excel, or Access, and its been around for, oh I don’t know, a few decades? I’ve seen entire departments run from Excel and Access applications. You can’t stop them from using these. I’ve seen desktop computers that used to belong to an enterprising employee 10 years ago, that built an Access application that became mission critical to a department, and the department has seen the employees turnover two or three times in that period. Nobody remembers who the original developers were, or even what it was running, but each newly appointed department head got the instructions to make sure that desktop computer remained powered on under their desk and hooked up to the network. God help them is this computer dies or something. And these scenarios are a nightmare for IT groups that get handed to them to support – but you cannot stop it. Much like that Jeff Goldblum line from Jurassic Park – Life finds a way.

 

jp93-eggs1These new tools just give the enterprising users a new means to create things that BI teams or IT groups are going to have to support. They are given tasks to run the business, and then the BI group doesn’t have the time or means to provide them the reports or analysis they need to meet those new milestones that leadership keeps placing on them. And, nobody likes a whiner, so they invent what they need outside of the process. Business is happy. Users are happy. IT is blissfully unaware. All they know is that they stopped emailing them asking for a status on their request and didn’t even miss the emails. Is this really such a bad thing? I mean, if the BI team built every single thing the business thought it needs to run then they would collapse under their own weight. Rather than cringing at these outlaw scenarios, if you look at them as a proof of concept exercise, and let the POCs that live life past a year or some determined amount of time that proves the reasoning and the needs were real, then really everyone who does these are helping out the BI team.

 

Rather than seeing these activities as competition or amorphous growth that cannot be supported, BI teams should looking to guiding these rogues in a way that helps keep some sanity to possibly taking over the project when it has matured. Choosing one self service BI tool and embracing it, training on it, training others on it, would be a much better alternative than leaving it up to the department and needing expertise on 5 or 6 different tools de jour. For one, it enables you to hire or train a resource for the BI team to assist users in developing their own projects and for taking over projects that have grown to big to be a department only project. Secondly, it provides some consistency to the rogue POCs so that the company looks like it knows what it is doing. Third, taking the lead to facilitate this movement means BI and IT can guide the company down the path to some degree, rather than being handed who knows what to support. Don’t fight the tidal wave. Grab it, embrace it, lead it. Sticking your head in the sand is never a good strategy.

post

Agreement Allows Vortisieze Technology to Resell TimeXtender’s Data Warehouse Automation

AARHUS, Denmark & BENTONVILLE, United States – September 2016 – TimeXtender, the world’s leading provider of data warehouse automation (DWA) software for Microsoft® SQL Server®, today announced a reseller partnership with Vortisieze. This agreement allows Vortisieze to offer the combined data warehouse and business intelligence package to their clients.

 

timextender-small-logoTimeXtender’s successful track record in helping companies with data warehouse and business intelligence has spread across the globe, and TimeXtender’s partnership with Vortisieze strengthens TimeXtender’s leadership in the Data Warehouse Automation (DWA). With more than 2,600 customers and various partners worldwide. TimeXtender’s Data Warehousing Automation platform simplifies the data warehouse process and minimizes the time spent on turning complex data into valuable information.

“Vortisieze has a great reputation for helping customers make better business decisions to compete in the marketplace,” said Heine Krog Iversen, CEO, TimeXtender. “By partnering with TimeXtender, this mission can be accomplished even faster and easier than ever before. The pairing of our TX DWA with Qlik will help their customers have access to corporate data, thereby realizing the benefits of the Discovery Hub in days rather than months.”

The partnership provides current and future Vortisieze customers an avenue to democratize access to corporate data, enabling business users and liberating IT.  TimeXtender’s TX DWA puts user-friendly data in the hands of the right people at the right time.  It protects the data in a secured and governed fashion while displaying the data in a stunning, analytical visual presentation, helping organizations reduce the gap between business and IT, and to realize the numerous benefits of a modern data infrastructure. This integration package also allows business users to independently and easily make changes and upgrades through drag-and-drop functions and without IT support.

 “Vortisieze has been helping companies build and deploy data management systems for many years,” said Cary Hague, Vortisieze. “This new alliance with TimeXtender now affords us the opportunity to help companies build and deploy the Data Discovery Hub.  We look forward to helping companies streamline their data warehouse and business intelligence systems, while reducing costs and strengthening operational efficiency.”

For sales or partnership information regarding this announcement, contact Kelsey Smith TimeXtender partnership manager, at ksmith@timextender.com.

About TimeXtender

TimeXtender has headquarters in Denmark and the U.S. The company has more than 2,600 customers across six continents using its data warehouse automation (DWA) platform, making it the world’s leading DWA solution provider for the Microsoft® SQL Server®. The company democratizes access to corporate data, enabling business users and liberating IT. It sells its products direct and through its global network of channel partners and is a Qlik Technology Partner. TimeXtender helps companies, from any vertical industry, rapidly deploy and automate their data warehouse solutions on a Microsoft SQL Server. It is fully compatible with Visual Studio and all associated Microsoft SQL Server tools and has a strategic role in helping customers save deployment and maintenance time and costs, while offering end-users a more robust and easier-to-use data warehouse and business intelligence system.

About Vortisieze

There is only one company in the world that is combining category sales data with customer sentiment data, weather data, US Census data, and third party marketing sources using state-of-the-art Hadoop “Big Data” technology and then layering the most advanced analytics platform on top for the most powerful, insights driven category reporting platform on the market.

We have over 50 years of experience in data warehouse modeling, data integration, category reporting, predictive analytics, MicroStrategy architecture, and Hadoop big data in Northwest Arkansas (Bentonville, Rogers, Springdale, Fayetteville). We build solutions that help you squeeze every penny of margin using data that nobody has tried to leverage before on a platform nobody is using for this. We think this is pretty exciting!

post

Is there ever a perfect storm for suppliers?

walmart-snow

In the article below, RetailWire talks with Weather Expert Paul Walsh on customer behavior, and what retailers are doing to balance things out.

“What almost always happens when you get a big event like this is you really see three phases from a retailer perspective,” Walsh told Retail Dive. “Actually, it’s really from a consumer perspective, and the retailers’ job is to be ready for their customers’ needs.”

Retailers don’t lose or gain sales as weather events hit, unless their supply chain is not prepared for the push ahead of the event. What this signals is that retailers are getting out ahead of these events using weather data, and suppliers are being increasingly asked to help anticipate supply chain strains ahead of the curve as well.

“The weather ate my homework” is no longer going to be a viable excuse in the coming months and years. There will be an expectation that a supplier network will need to be out ahead of this. It won’t matter if you are a top tier supplier maximizing your category, a mid-tier supplier scratching and clawing for their business every day, or a small supplier just trying to keep up. The forecasting models are becoming more and more accurate. Not having your products attributed to weather sensitivity will be a hindrance.

oos-walmart-snowstormIt’s also important to consider “just weather data” may not be enough. Feature engineering both the weather data to tailor it to your products and your products attributes may be required to extract enough insights as to what weather patterns and events are effecting your sales. Make sure you have people on board that can do this with your data, and it may take some experimentation, since no two product assortments are the same. Having the data at the same level as your geography dimension also helps take some of the burden off of your analytics platform. Its a lot of data, and most of it comes at the weather station level.

Have I mentioned yet that we can do this for you? We can provide weather data at the zip code level, and we have experts on staff that can help with your feature engineering, as well as your reporting and data mining.

You can read the whole article here

Please contact us today to see how we can help you with your BI weather challenges.

post

Mobile Development vs MicroStrategy Mobile

Mobile-Application-Development

I had a potential customer ask me yesterday if we could build mobile apps. Apparently they had just spent a lot of money on an app that would allow them to collect data in the field, but it did not integrate with any of their shipment data or POS sales data to complete the picture for their field personnel. This company also did not have the resources to build any kind of custom app from scratch themselves. So, if you are thinking about taking this feat on, let me break it down for you in a few high level steps.

There are many scenarios that you can walk down, but I am going to walk down two specifically: Custom app vs. MicroStrategy mobile app.

Scenario 1 – Building a custom app from scratch.

First off, you are going to need a good overview on iOS development. Try here for starters. When you go down this road, you are going to need a Mac to do your development on. You will also need a developer account with Apple to be able to publish the app. If you want to be backwards compatible, you may need more than one Mac to test on, as the XCode environment is tied to the OS (from what I can tell). You also will need an iPad or two, or three for testing. If you want to support iPhones, you will need some of those. What about the version of iOS? We are currently on 9.x. Do you want to support 8.x as well? While there are testers for some of this in xCode, if you want to make sure your app works across all of these environments I think it is a good idea to develop a test plan on actual HW so that your app isn’t flakey.

On your app side, you are going to be writing a lot of Objective C code to run the app, but you are also going to need a service in the background to dish out data and be the backend for the app. I doubt you would want the app to connect directly to your database. This service should also handle secure logins, passwords, user management, resetting a user password – all of the plumbing that will enable a user to mange the app, their account, and themselves. It also needs to grab data from the data warehouse and package it back to the app. You might need to compress it to make the app more faster.

Now, once you’ve climbed through all of that, you get to manage change management coming from user feature requests, from corporate, from bugs. You get to roll out new versions, craft a test plan to make sure it all remains backwards compatible with older versions of iOS, across all apple devices. To keep up, you may have to juggle a roadmap with multiple versions in play at various lifecycle stages – or in other words, you may be performing user acceptance testing on version 2.5 while you are working on publishing version 2.4 to the app store, as well as scoping changes to version 3.0 to be released next quarter.

I would not say any of this is rocket science, but it can grow to be quite an undertaking if you want to do it right. Wait – where is your Andriod app at? Corporate CFO has an android and wants his version for his phone. Where do you start for that? Now, remember that app that you thrashed in the comments because it was so buggy last week? Feeling even the least bit sorry for that company if this is one or two people trying to keep up with all of this?

Scenario 2 – MicroStrategy Mobile

Now that your head is spinning from trying to develop and support a custom app, there is a bright side to all of this – MicroStrategy Mobile. There are lots of other platforms, and this article could go on for days, but we have direct experience in MicroStrategy Mobile so we will give a glimpse of this one to compare and contrast.

First off – you will need a MicroStrategy environment. This of course is not free – you will need to get an enterprise license for this and each user will need a license. Second – you will need to develop your data objects. This also is not for the faint of heart. Most companies do all of this because they want slick reports, dashboards, and gorgeous data visualizations., regardless of mobile or not. This is pretty much MicroStrategy’s bread and butter. It handles all of the service back end, scheduling, report automation, security, throttling, and presentation. You just need to get your data into a data warehouse. There are lots of strategies for BI – but, if you go down the MicroStrategy route, then you inherit a Mobile strategy second to none.

All of the reports you built for your monday morning dashboard can translate directly into a mobile app with just a small amount of effort. There is no source code you need to master. MicroStrategy can handle much of the iOS compatibility and hardware testing. It’s almost like a buy one, get one free. You get enterprise class reporting along with enterprise class mobile.

MicroStrategy also has transaction services, which allows you to input data on the iPad. Need to capture store shelf quantity, or survey questions? No problem. It can capture data alongside all of your enterprise data warehouse metrics for a complete, 360 degree dashboard. It can show images, take pictures, capture data, report data, drill into your data, visualize your data in graphs and charts. You can build an entire customer service app – just in MicroStrategy – with your company icon and logo.

Summary

Now, if you just needed a mobile app, is this the easier route? Depends on how you look at it. There is probably equal amount of effort getting both scenarios up to speed. I won’t lie and say that MicroStrategy is easy. The payoff comes downstream when you need to support your app. If someone requests changes to your app, you can make a change to your MicroStrategy dashboard inside of MicroStrategy – without needing to recompile, test, and publish your app to the Apple app store. This change, depending on the significance, could literally take you 2 minutes to log in and change something minor. Want to roll out a version of this app for a new customer? Copy, paste, and change the logo – again, maybe a 10 minute change. Because of the object oriented development nature of MicroStrategy, each dashboard will inherit all of the building blocks in the foundation you build. So if you formatted a date wrong, you go change the date attribute. All of your reports, dashboards, and mobile apps then inherit the change – no need to touch them.

Hours or days – not weeks or months. No objective C code to maintain. No API service backend to maintain.

80% of what you build in MicroStrategy is reusable. This is not the case with Tableau, Qlikview, SSRS, Crystal Reports, or custom ASP.NET portals. This is why we lead with a MicroStrategy solution. If we build a customer a neat dashboard to be consumed in a web browser, and the CFO determines they want it on their iPad, we just have to copy, paste, and then do a little resizing so it fits nicely and viola – instant mobile app. Maybe less than a day’s work. If you are building a custom app from scratch – where is your git repository hosted at again?

If your organization could benefit from a BI platform to deliver reporting,dashboards, and data discovery – and also needs a mobile app strategy – then this seems like a no brainer to me. Even if you think it might be useful down the road, then having a combined strategy for BI and mobile makes sense. If you go down the road of separate BI and mobile, then you are eventually going to have to join them up, and it will be twice the support at that point. Twice the cost and twice the fun.

Please contact us today to see how we can help you with your mobile app and BI challenges.

post

Drawing the Wrong Conclusion: Why #BigData Alone Is An Inadequate Source Of #CustomerIntelligence | #CPG

Naturally, anytime an article’s headline is about Big Data I take notice.  And especially so when it claims to tell my why Big Data is inadequate.

So after digesting this information, please allow my a couple of minutes to discuss why the author totally missed the mark on, and the point of, big data.

He makes three main points.  As he puts it, “Here are three reasons why a lot of investments in big data fail to deliver ROI.

  • Most companies don’t know how to use big data for strategic decisions.

Companies need to learn how to manage information, analyze it in ways that advance their understanding of its customers, and then act intelligently in response to new insights.

“Companies don’t magically develop those competencies just because they’ve invested in high-end analytics tools. They first need to learn how to use the data already embedded in their core operating systems, much the way people must master arithmetic before they tackle algebra,” information science academics Jeanne W. Ross and Anne Quaadgras from MIT and Cynthia M. Beath from the University of Texas at Austin wrote in the Harvard Business Review.

One reason that companies are unable to benefit fully from their investments in big data is that “management practices haven’t caught up with their technology platforms,” according to Ross and Quaadgras. For example, companies that have installed digital platforms, such as enterprise resource planning (ERP) systems and customer relationship management (CRM) systems over the past 10 to 15 years, haven’t yet taken full advantage of the information they make available. A cultural change is needed within companies so that “all decision makers have performance data at their fingertips every day,” Ross and Quaadgras write.

As an example of a company that uses data effectively, Ross, Quaadgras and Beath cite 7-11 Japan, which provided its employees with daily sales reports and supplemental information such as weather forecasts, what sold on the last day the weather was similar, what sold the previous day, what sold on the last the same date a year prior, and what was selling in other stores. Importantly, clerks were connected to suppliers “to encourage the development of items that would suit local customers’ tastes.”

The 7-11 Japan story was not about big data or investments in data, but about a lot of little data. “It’s about betting your business success on the ability of good people to use good data to make good decisions,” the authors wrote. “Empowering employees in this way, and arming them with the data they need, helps them make better operating decisions on a daily basis. It can also lead to a constant stream of innovation.”

Big data, as it’s described today, is not the answer to all questions—and it’s no replacement for the on-the-ground decision-making of real people interacting with real customers.

 

First, no one in the “big data” arena, that I have read has suggested that any technology develops competencies for anyone – only people can develop competencies.  But this reminds us of a common theme this week – a CPG category or sales manager must have a marketing strategy, which then drives questions, that dictates the data to be mined.

Second, he writes, “The 7-11 Japan story was not about big data or investments in data, but about a lot of little data.”  Hello?!  Here’s where he doesn’t understand big data – big data is a LOT of little data.  The ability to pull in unstructured data with the existing structured data and rapidly blend the data (i.e. data blending) to draw new insights.  That is the purpose of the technology and why it exceeds the capabilities of rigid DSRs built with old data warehouse style databases.

Finally (on this point), he writes, “—and it’s no replacement for the on-the-ground decision-making of real people interacting with real customers.”  He is correct – no technology is sufficient to replace real people – that characteristic is not unique to “big data.”  People, whether they are consumers in your retailer’s store or the buyer you deal with at the retailer home office, do business with people – not technology.  We use technology to facilitate fast, and sometimes global, interactions.  He criticizes this technology for sharing the common characteristic of all technologies – what’s the point?

 

  • Big data doesn’t provide a complete picture.

Another telling example of the danger of relying on big data alone comes from the world of social media analytics. Seen widely as a holy grail for companies seeking insight on their customers, social media analytics falls short on several fronts. Consider this: 85 percent of social media updates come from so-called “enthusiasts”, but only 29 percent of a typical company’s audience are enthusiasts.

The vast majority of social media users are in fact relatively quiet. Companies can’t hear them, although they’re listening to you. That means that social media analytics can mislead companies about what matters to customers as a whole, when in fact what they’re seeing is only a very thin slice of their audience.

Colin Strong, a leading consumer researcher in the U.K. emphasizes this point in his 2015 book Humanizing Big Data. “Since Twitter users make up only about 10 per cent of the U.S. population,” he notes, “some demographic or social groups won’t be represented. The result? More data … does not necessarily mean more insight as it does not necessarily reflect real life.”

People who spend a lot of time online are typically younger, better educated and more affluent than the overall population—again, offering many companies a limited view of existing and potential customers.

Note:  He makes this argument by coming to a false conclusion about big data from the flaws he sees in social media data.  Social media data != big data.  Social media data is a subset of big data.  One thread in the fabric creating a complete customer tapestry.  Not understanding the definition of something will inevitably result in false conclusions.

Premise: Ducks are birds.
Premise: Ducks swim in the water.
Premise: Chickens are birds.
False Conclusion: Chickens swim in the water.

  • It lacks the “why.”

Big data can reveal much about what’s going on, when it happens and where it happens. But we haven’t really arrived at the day when big data can reliably tell us why customers behave in a certain way.

See my final point on issue #1.  No technology does our thinking for us.  What technology delivers, especially big data technology, is the data (information) much faster – allowing CPG marketers to analyze that data (again with BI technology), so to develop actionable insights much sooner (a human function).

As computing advances and analytical tools progress, we may get to that point. But for the foreseeable future, big data is only one tool in the marketer’s toolbox. Market research that involves more direct human-to-human interactions with consumers will still be vital. Big data will only take us so far, and at some point a human perspective needs to join the effort.

For marketing departments to derive value from big data, they have to get better at leveraging social science, data analytics and consumer insights. Understanding the nuances of customer behavior—the motivations, or the “why” behind behaviors—gives us true insights. And those cannot come from a centralized and isolated big data department.

 

  • Conclusion

Big data surely has a role to play in gaining insights into the behavior of these empowered customers. That’s why enterprises are pouring billions of dollars into the big data industry.

But big data doesn’t have all the answers—at least not yet, and perhaps never. Companies need to respond quickly to identify changes in customer behavior and take action to address their concerns.

In short, the emergence of big data doesn’t change the fact that people matter. A human touch is still integral in business today. Big data can offer some answers but continual human-to-human connections are also needed to fully understand rapidly evolving marketplace.

My conclusion:

While in agreement with his statement, “the emergence of big data doesn’t change the fact that people matter. A human touch is still integral in business today.”  That has always been, and will forever be, true – regardless of the technology used to gain insight into the consumer’s behavior.  People do business with people.  Relationships always matter.

The author lacks an understanding of “big data,” doesn’t know the definition of “big data,” and criticizes the characteristics of “big data” that all technologies share.

This article reaches the wrong conclusions for all the wrong reasons.

 

If you are interested in finding out how big data can really give you the tools you need to outpace your competition please contact us today.

 

 

Source: Why Big Data Alone Is An Inadequate Source Of Customer Intelligence

 

 

 

#BigData

#BigDataAnalytics

#CategoryManagers

#CPG

#CPGMarketing

post

#CPG: 10 Reasons Why Now Is the Time to Get into #BigData

Rick Delgado is a new technologies freelance writer. In this article he takes an objective view of Big Data and lays out 10 reasons why now is the time for Big Data. My observations are italicized below.

1. It will keep your data secure

Being able to completely map your data out in front of you will make you better at analyzing potential threats. You can easily ensure that the most sensitive data you have in your system has all of the necessary security features it needs to stay well protected and within any sort of regulations that your business has to adhere to.
Many BI tools have provided for this sitting on top of the data – however – the big data structure allows this to be mapped into the clusters where data lives.

2. It opens up brand new revenue sources

You will gather a ton of insight into your part of the market. This insight is valuable, and not just to you. Selling out non-personalized industry data about trends in the market can bring in a ton of money from any other businesses operating in the same portion of the industry that you are, making it a great way to bring in some more funds.
While this is not always possible for a CPG company, for example, to do when retailer-sourced data is in the mix there are other opportunities at the enterprise level.

3. It’ll give you an advantage

Businesses are built on tradition. Any industry is going to have years of tradition that believe that one way of doing things is the right way and if it isn’t broke, don’t fix it. One important value that big data has is that it lets you really examine and analyze preconceived notions about aspects of a business you may have never even considered. It will provide better data when it comes to experimenting and trying to innovate, meaning that you’ll be able to get a much better advantage over your competitors.

4. Better Visuals

Big data requires cutting edge data visualizing tools in order to translate all of those numbers and data points into something a bit more tangible. This will increase overall usability that can be utilized by people in the business themselves or their end users.
There are increasing numbers of tools available for the user to create insight from their data lake – Vortisieze prefers MicroStrategy but ultimately is agnostic toward the BI tool selected giving you maximum flexibility.

5. It’s very easy to set up

Big data used to be something that only big corporations could afford to get into. Luckily, there are alternatives that can bring the benefits of big data to a company of any size. Hadoop is a great open source framework that can handle large amounts of data. Hadoop works with Excel, which most businesses already use.
The entry point is such, especially with the ABC of business (Analytics, Big Data, Cloud Computing), that retailer sales/support offices can easily add this as a budget item without involving their IT division.

6. It helps your business evolve

One of the best things about big data is just how scalable it is. Getting the right tools means being able to convert not just number data, but also text, audio, and video files to find patterns that can give a business a ton of insight into the market. Investing in big data as a small company means you’ll be able to easily handle all the data easily that comes with growth.
You begin seeing your business as your customers (the ones buying your products from the retailer) see your business.

7. It can significantly cut back on maintenance

Businesses that rely on large pieces of equipment often spend tons of money when it comes to replacing and maintaining them using predetermined data that tries to predict how long they’re going to remain efficient. Big data allows you to get rid of rounded averages and replace them with specifics, allowing you to squeeze even more life out of machinery that still has plenty of use left.
And with cloud computing, also called data-as-a-service, there is no equipment involved to maintain.

8. It brings you closer with your customers

The customers of today are a lot different than in the past. The rise of the internet allows them to thoroughly and tirelessly research a product before buying and to communicate with tons of people about which brand they should do business with. Big data allows you to better profile these fickle consumers and figure out specifically what they want.
See comments to #6 above.

9. It’s easier to analyze risk

There’s more to business than running your own company effectively. Every business is just one in a large industry that must regularly compete and innovate in order to stay ahead of the rest. Utilizing big data to analyze things like news articles and social media will give you cutting edge information about the biggest and latest developments in your industry.

10. You’ll be able to improve your products

Big data is a key that’ll explain specifically what your consumers really think about your product. Big data is even being used in medical research for companies that do personalized medicine or companion diagnostics, and need to analyze large amounts of biological data. You’ll be able to use your insight to easily get a better picture of your customers based out of different geographic areas and belonging to different demographic groups. Once you’ve seen how the product is perceived, you can easily raise efficiencies in key areas along the product process.
These are extremely valuable insights to present to your retailer buyer – enabling your company to rise above the noise from your competition.

 

Source:  10 Reasons Why Now Is the Time to Get into Big Data

#CPG

#CPGMarketing

#BigData

post

#TextAnalytics – The Next Generation of #BigData

In this article Jeff Catlin of Lexalytics lays out the case for text analytics and its importance to the rising interest in big data. This points to the future where sentiment data coming from social media, much of which is unstructured, can be blended with the structured data from retailers, e.g. POS, inventory, et al, to give insights into brand awareness and acceptance, and sales volume changes.
The link to the article is below and is well worth reading – below is a synopsis of his major points.

Big Data

Sensors, tweets, emails, web clickstreams, CRM information, supply chain tools – data is flooding into every business, and the businesses that have the most facile processes for divining actionable information from the deluge are going to be the businesses that make the most money.

 

Unstructured Data

If it can be counted, it can be analyzed. If it can be analyzed, it can be interpreted. But what type of count or interpretation can be made from a voice recording of a customer service transaction? How are tweets or prose to be interpreted? What type of information can be gleaned from customer product reviews? What happens when those reviews are videos?

Unstructured data is a large part of big data. You can get a lot of information from purely structured data, things like the Click Through Rate (CTR) and conversions from an advertising campaign. But that’s not going to give you a view into what is actually being said. What is the conversation? In order to delve into the dialog, and whether it is a positive one for your business, you have to get into the unstructured side of things.

 

Big Data for Unstructured Text – Text Analytics

If structured data is big, then unstructured data is huge. The generally accepted maxim is that structured data represents only 20% of the information available to an organization. That means that 80% of all the data is in unstructured form. If businesses are gaining value from analyzing only 20% of their data, then there is a massive potential waiting to be leveraged in the analysis of unstructured data.

Unlocking this potential represents the next Big Data challenge.

 

The Business Value of Text Analytics

Identifying the “who,” “what,” “when,” “where,” “why,” and the sentiment of the conversation converts unstructured data into structured data, and enables businesses to listen to all of the conversations.

Text analytics can be used to develop a better understanding of the likes, dislikes and motivations of the customer. Changing loyalty program incentives to match customers’ desires can improve customer loyalty and increase sales.

 

The Coming of Age of Text Analytics – The Next Generation of Big Data

It can seem like a challenge to keep an ear to the ground, listening to conversations about your business, competitors, customers and suppliers. But if you’re not listening, you’ll be surprised when the winds change. While sometimes the surprise is good, often it is not. And when negative conversations take place, the impact to the business can be drastic.

 

Source:  Text Analytics: The Next Generation of Big Data

 

#TextAnalytics

#BigData

post

#DataWrangling – How #CPG #CategoryManagers Lasso Their Data Without Getting Gored

If you are a category manager or captain in the Walmart supplier arena, chances are you have become an expert in Excel. Without knowing it you have been data wrangling, and why not, what other tool enables you to combine data from such disparate data sources any easier? Granted, it’s work you have to do on a regular basis, and if these awesome spreadsheets and dashboards become popular in your organization, you get to refresh them on a regular basis, but that’s just the cost of doing business. If you have been lucky enough to get to use a BI tool like Tableau or MicroStrategy 9, then some of this work has been streamlined for you. Now, once you get your data refreshed, the visualizations can fall in line very easily. Getting the data refreshed is not always so easy though. MicroStrategy has traditionally been IT focused, with enterprise grade everything, focusing on data governance by the IT organization, while Tableau has focused in on the business department or user, that needs cool visualizations, but may not be the best at getting data into the tool in an automated fashion, but you can just whip up an excel spreadsheet and link it in. Viola – presto magic dashboards. In essence, you had to trade enterprise for ease of use.

2015-06-17 11_22_27-ReadyTalk Conferencing -Any data, quickly and easily

With MicroStrategy 10, that is no longer a problem. MicroStrategy effortlessly blends structured warehouse data (read IT generated and governed data) with data from your own pocket. Build something popular they want refreshed on a regular basis? Fire it off to the Administrator, and they can recreate what you built to auto-refresh with each data load. A lot of what you build is a one-off to answer a buyer question about on-shelf availability, or you’ve got some market basket data that is driving a question. It’s not necessarily something that needs to be built, refreshed, and maintained as a corporate dashboard or report. But, you do want to blend this data that is loaded each week in your enterprise data warehouse, like your POS sales or your historical inventory. But what if the data is not formatted correctly to report against?

You could make the argument that you need to load everything into the data warehouse, but why would you do that if you have a one-off analysis and you may never need that data again. Only one DSR makes it pretty easy to add data like it’s tissue paper for integration with the rest of the demand signal data for use in MicroStrategy, and that is the Vortisieze DSDH (Demand Signal Data Hub) – mostly because we are using Cloudera as the backend. If you knew you were going to run these reports on a regular basis, or needed them refreshed – then by all means add them to the data warehouse, but now the choice to not add data to the data warehouse does not default you back to Excel – you can do this in MicroStrategy Desktop, blend it with the enterprise data you have come to trust, and refresh this on a weekly basis with a few mouse clicks.

What enables this is the Data Wrangling feature that is new with MicroStrategy 10 that is not available in any other tool I have seen. See, one of the benefits of utilizing ETL (Extract, Transform, and Load) to load data into your data warehouse, is that your ETL team will cleanse and harmonize your data so that it lines up correctly with the rest of your data. States won’t be a mish-mash of two letter abbreviations or full state names. Data won’t be mixed formats – that is the whole point of ETL. So, when you skip the ETL team, you are on your own to cleanse and harmonize your data. Traditionally this meant dropping your data to excel and spending a few hours searching and cleaning it up so that the reports made sense. MicroStrategy 10’s new data wrangling feature will do some minor cleanup of local data sources for you without the need for an ETL team.

Now, you can have the best of both worlds. MicroStrategy 10 has been designed to give the business user the most flexibility in data sources, and not rely on your ETL or IT team to cleanup local dirty data, but still be able to leverage corporate data sources that have been cleaned and vetted. Got a marketing data set direct from twitter? Want to marry that with POS sales or weather? I can’t imagine these tasks can get much easier now, and you have more flexibility than ever to bring in your ETL team when they are truly needed. With the ability to go and buy a single license of MicroStrategy 10 for $600, there is not much standing in your way of being the organizational rock star of analytics. Plus, now you get to add the cool title of “Data Wrangler” to your credentials.

 

#DataWrangling

#CPG

#CategoryManagers

post

#DataBlending, #BigData and #BusinessIntelligence

There are many new buzz words buzzing around these days. Terms such as data blending, advanced analytics, big data, cloud computing and business intelligence. Sometimes it is easier to learn a foreign language than to decipher the meaning behind these terms.

As a CPG sales analyst or category manager what is your primary purpose? Increase your brand’s revenue and grow your real estate on the modular. To do so, you aim to create and maintain a competitive advantage with your buyer over your competitors.

Making better and timelier decisions help to gain and maximize any advantage. Drop or increase price, introduce a new product now or six months from now, which audience should be targeted. These decisions, made with the buyer, rely on accurate data and analytics to produce insights – thus business intelligence.

Business intelligence and analytic solutions address these challenges by allowing for easier information discovery and analysis, making it possible for decision-makers at all levels of an organization to more easily access, understand, analyze, collaborate, and act on information; anytime and anywhere.

Remembering your school days and the teacher helping you mix blue paint with yellow to make green paint – the fundamentals of data blending is the same; take one piece of data, mix it with another, and create something different and more appropriate – a new output for analysis and evaluation. This provides new ways to extract value from multiple data sets, discovering patterns in the data, demonstrating more insight to inform the decision-making process.

A few short years ago this activity would have taken sales and business analysts weeks to do this. In short – it would not have been done and if it had the data was sufficiently aged so immediate action was impossible. Today, Vortisieze is blending weather data with POS, inventory and even store straits to discover new patterns that may result in actionable insights.

Working closely with industry leaders such as MicroStrategy and Cloudera we are creating data blending and advanced analytics solutions. Armed with these solutions, we are able to recommend and implement the right data analysis process to meet your business need. Harnessing the power of data blending and advanced analytics means that CPG companies can unlock the insights gained from business intelligence.

Looking over the landscape of business intelligence and analytics solutions on the market it is obvious that the field is crowded, but not all have combined the new technologies with the retail expertise necessary to be right for your business and the objectives you want to achieve. At Vortisieze, because our founders have decades of combined experience in all levels of retail BI – IT, category management and analytics – we understand your business, not just what you do but also how you do it. By collaborating with you we then understand your current and future goals. Vortisieze is able to assist you in identifying the most appropriate of the solutions available to meet your strategic goals.

For more information about Vortisieze and the ABC of business (Analytics, Big Data and Cloud Computing) please contact us today.

#DataBlending

#BigData

#BusinessIntelligence