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#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

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#MicroStrategy 10 Adds New #Hadoop #Analytics Capabilities

The leader in the BI analytics platform sphere, and the preferred BI tool by Vortisieze, MicroStrategy is now allowing users to enjoy the richness of data that Hadoop allows.

  • MicroStrategy Inc.’s has launched a major upgrade to its namesake business intelligence platform that promises to help organizations make more out of the vast troves of data they’re storing in Hadoop. That’s done through improved connector bundled natively into the new release.
  • MicroStrategy 10 enables analysts to manipulate imported information using new search and visualization functionality that the company says removes the need to use external tools for that job. That avoids the overhead associated with moving files back and forth, which can amount to significant time savings at the petabyte scale in which many production-grade Hadoop clusters operate.
  • The company promises to take even more delay out of the equation with optimizations to its multi-dimensional analytic algorithms, which now makes it possible to put more data into the logical constructs used to group similar metrics for faster queries. MicroStrategy said that the update has helped PayPal, Inc. achieve sub-second response times for 400-gigabyte workloads.
  • Analysts can take advantage of that performance through the improved interface also introduced in the new release, which is extended to mobile devices with a new companion app that can track the the performance of each user. The client also includes a badge-based security system that allows administrators to control who can access what and how.

Source:  MicroStrategy 10 brings new analytic capabilities to the Hadoop table

#MicroStrategy

#Hadoop

#Analytics

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#MicroStrategy 10 Secure Enterprise Now Generally Available Worldwide

While not the only BI tool available in the Vortisieze offering, MicroStrategy is the preferred BI analytics tool for the Vortisieze data-as-a-service.

MicroStrategy 10 provides enterprise-grade analytics, mobile and security software combined in one groundbreaking platform.

MicroStrategy 10 Secure Enterprise contains a host of new features and enhanced functionality:

  • Revamped data discovery offers enhanced exploration and visualization capabilities on both Mac OS and Windows. New built-in data wrangling capabilities enable users to quickly prepare data for analysis without using other tools.
  • New governed data discovery makes it simple to promote dashboards from the desktop to the enterprise, providing a seamless path from self-service analytics to enterprise BI.
  • New native Hadoop access makes analyzing petabytes of multi-structured data easy. MicroStategy 10 offers native HDFS connectivity within a complete enterprise analytics environment.
  • Bigger, better in-memory performance lets users put more data on parallel-partitioned in-memory cubes, so organizations can run faster queries across larger volumes of data.
  • Completely redesigned HTML5 interface makes self-service analytics faster, more intuitive, and easier to use, so users can quickly connect to any data and drag-and-drop their way to business insights in an instant.
  • New Operations Manager enables administrators to save time and drive efficiency by managing and monitoring all of their environments from a single interface.
  • Cutting-edge platform security, powered by biometric and multi-factor authentication, provides enhanced security for every method of analytics delivery, conveniently and seamlessly.
  • Convenient user verification with a smartphone app replaces the need for users to log in with a password.
  • Out-of-the-box employee productivity app, built on MicroStrategy’s proprietary telemetry database, gives managers powerful insight into employee activity and performance.

Version 10 underscores MicroStrategy’s commitment to serving the enterprise analytics needs of global organizations.

 

Source:  MicroStrategy 10 Secure Enterprise™ Now Generally Available Worldwide

#MicroStrategy

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#BigData Will Power #CompetitiveAdvantage for #CPG Business

87% of enterprises believe that big Data analytics will redefine the competitive landscape of their industries within the next three years

The combination of social networking as a way of life, and the ever-growing number of devices on which people stay connected, continues to generate untapped sources of data that could help businesses compete more effectively.

Decreasing cost of both storage and computing power have made it feasible to collect this data – which would have been thrown away a few years ago. Today, enterprises want to capture and manage large amounts of information from multiple sources both structured such as ERP, CRM and database systems and unstructured including web sites, social media and streaming.

“More than ever, growing adoption in mobility, new types of applications and cloud services are driving organizations and consumers to store, manage, safeguard, analyze both traditional, structured data as well as unstructured or semi-structured data generated by multiple applications running on smart phones, tablets and all other computers. Whether it is called Big Data or Internet of Things, we all want to gain more insights on how to run our business more effectively. Technology companies such as Microsoft hold the belief that it is more crucial to embrace advanced analytics that will enable everyone in organizations to gain actionable insights and gain competitive advantage by benefiting from predictive and prescriptive analytics,” says Aydin Gencler, Director Product Marketing, Middle East & Africa at Microsoft.

Big Data main tool Hadoop was driven by the exponential growth in the volume of unstructured data from Big Data analysis and the ability to access data at high speed with reduced costs compared to traditional RDBMSs.

A brighter future for Big Data

 

Analytics, big data and cloud computing will continue to transform the business landscape for the foreseeable future.

#BigData

#CompetitiveAdvantage

#CPG

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From #BigData to #SmartData

After reading the article “From Big Data to Smart Data: 10 tips for business leaders” – which discussed the ABC of business – analytics, Big Data and cloud computing – three points really grabbed my attention.

  • Size does not matter
    • Even smaller companies need the Big Data advantage; it’s a myth that only big companies stand to gain from Big Data. For example, small financial trading companies still deal with huge volumes of rapidly-changing data. The future will not be won by big companies pitted against smaller ones, but smarter companies against less intelligent ones. However, more work needs to be done to pitch Big Data solutions in the language of the SMB.
  • Go beyond transactions to customer journeys
    •  Big Data allows visibility into the entire customer decision-making journey, and thus opens up the possibility of predicting purchase and follow-through behaviours. It also allows the creation of a wider range of customer personas, with more detailed and deep profiling.
  • Differentiate between the old data and Big Data advantages
    • Traditional business IT metrics have always focused on issues like better conversion rates and longer retention. New results offered by Big Data include real time tracking and response, new metrics such as buzz factor, and innovation via data-led creation of new products and services. Successful companies ahead of the learning curve can even create new Big Data services out of their competencies.

Ok, here’s a fourth that couldn’t be left out.

  • If you have it, keep it
    •  Some CIOs are not sure how much data to archive, and for how long. It is probably better to keep all the data you have because the questions and frames for interpreting the data may arise only in the future. However, in some sectors like finance and healthcare, regulations and government stipulations may require all records to be maintained at all times. Within the organisation, the CIO usually owns the data (in sectors like telecom), or the CMO (retail).

#BigData

#SmartData

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#Walmart #POS #WeatherData Analysis in MicroStrategy


There are lots of ways to analyze your POS sales against weather, but it might be good to first determine if there is even a correlation between the two. If you’ve got weather data and POS data in your DWH, you can achieve this relatively quickly by using a weighted trend graph in MicroStrategy’s Visual Insights. As you can see in the screenshot above, we created a data set with Walmart week, some POS metrics, and some weather metrics – the one we are interested in for this set of products is Average Temperature. With WM Week as the x-Axis and POS sales as the y-Axis, we then have the ability to color the line by Average Temperature, and we weight the line with precipitation. As the line moves from red to blue the temps get cooler, and as the line gets thicker we see more total precipitation across the country for that week.

At a high level, this graph doesn’t give us anything we can action directly on. However, it does seem that as the country cools off we sell substantially more product. With a little more work we can add some drill downs to state or store and look at temps down to store level to see if each store exhibits the same behavior or if they seem unaffected.

Not all products have a correlation to weather, but these seem to, so next post we will dive deeper into how weather seems to affect sales, and we will try to add some more interesting metrics to help identify outliers or patterns we can predict. Feel free to comment or send suggestions on how you would like to see this dashboard evolve to marketing@vortisieze.com and we will see if we can incorporate your suggestions into the dashboard.

#Walmart

#POS

#WeatherData

 

 #Vortisieze Technology Releases First Software Product for #CPGMarketing

For Immediate Release

Vortisieze Technology LLC
479-633-7821
sales@vortisieze.com
www.vortisieze.com

Lowell, AR – March, 3/9/2015 2015 – Vortisieze Technology has released their first software application, Filter Manager. This application automatically updates filters built in the MicroStrategy business intelligence tool based on a calendar table, and is completely customizable and extensible. For analytics that do not follow a standard calendar format (like a Walmart fiscal calendar for instance where the year beginning date can change based on an odd number of weeks every four years), it can be difficult to build rolling date filters for scorecarding metrics, or in some cases downright impossible. This application turns that complex logic into simple date filters that are then easy to use in your reports and metrics.
This software rounds out their application stack that provides item-store-day level analytics built on top of Cloudera Hadoop and MicroStrategy. By combining these tools with best of breed analytics built in MicroStrategy and tools like Filter Manager, Vortisieze has created a fast, agile data platform that can react to your changing business as fast as you need it to. By Partnering with Cloudera as their Hadoop provider they are able to scale to any size of dataset that is needed. Data that was just a dream is now possible, from correlating sales performance to social data and weather data, to finding relationships between SKU-Store performance and hospital mortality or unemployment rates, Vortisieze is pushing the boundaries of thinking that can be used to increase sales.

Vortiseze Technology LLC builds analytics platforms in MicroStrategy and Cloudera-Hadoop. Filter Manager is their first go-to-market application that can be purchased on it’s own to use with your own data warehouse or in conjunction with the Vortisieze MicroStrategy-Cloudera application that helps CPG companies manage their business with very large retailers.

Vortisieze Technology LLC is a software and data analytics company with over 30 years total experience in data warehousing, MicroStrategy solutions, software development, Walmart category management reporting and Cloudera implementations. Based in Northwest Arkansas they are centrally located to service their customers who deal with very large retailers.

If you are interested in Filter Manager or our complete analytics suite please email sales@vortisieze.com or call us at 479-633-7821

 

# # #

 

#Vortisieze

#CPGMarketing

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Ten Secrets to Win with #Analytics

BI-chalkboard

Nearly every organization today uses analytics. But not every organization is getting as much out of its analytics as it could. So, how do you truly excel with analytics to deliver the best support for decisions?

  1. Don’t fail to plan:  Doesn’t sound like a secret at all does it? Well, too feworganizations have spent the time to begin with the end in mind. The most successful companies always begin their analytics projects with a clear vision of what is the target. The key stakeholders should be aligned by writing down and sharing:
    • What you’re trying to achieve
    • Who you’re trying to reach
    • Why it matters
    • How you’ll measure success
  2. Use your analytics tool to uncover data quality issues:  Don’t let the desire for perfect data be the barrier to very good data. Instead, use your analytics tools to spot abnormalities in your data and learn from them. Then, work with the people who own the data and share your insights; thus helping them fix their processes. By forming partnerships, you can significantly improve your data quality over time.
  3. Use Good Design:  Most of your data consumers visualize data to understand it, so aesthetics play an important role. Like an interior decorator, a good designer can help you develop an intuitive and effective user experience and a great look and feel for dashboards and visualizations. However, data visualization best practices always outrank aesthetic design – every time.
  4. Repetition, repetition & repetition – learn through play & through doing:  Your worst data model is your first one – nobody creates a perfect model for their data on the first try. And that’s OK. Truth is, looking at your data from different angles can teach you a lot about it. Let everyone connect with the data in their own ways — you’ll be amazed at what they discover. Use what they do to inform your strategy (back to #1).
  5. Be your loudest evangelist!  Some software projects are mandatory for users, however, adoption of analytics is voluntary in most organizations. So, if you want people to know you have built a better mouse trap, act like Guy Kawasaki and start promoting it. Recruit your marketing department and sell the value of analytics throughout your entire team and organization.
  6. You need a champion:  champion-awardFind an influential person or team that has an unmet need and empower them with analytics. This can turn them into true believers by showing them what’s possible. Then turn the spotlight on their success to prove the value of analytics to the rest of your business.
  7. Build a Cross Functional Team:  Selling analytics is simple when it becomes easy to repeat successes and avoid failures. Bring together a cross-functional team and put them in charge of:
    • Deciding the role of analytics
    • Defining the standards and tools
    • Identifying best practices and gaps
    • Iterating and improving the solution over time
  8. Have dual processes:  Changing the method of measuring KPIs or profits requires taking your time and getting it right. However, sometimes you have a unique and urgent situation and must develop an app right now to analyze it. Put in place different processes for both scenarios — and accept the fact that it’s OK to build temporary throw-away apps for one‑off projects.
  9. Reports are so 90’s:  Don’t be like most BI deployments that tend to focus on delivering the same out-of-date reports that has been around for decades. Simply describing the situation presented in the data does not provide analytic value for decision makers. You must answer the ‘why?’, not just the ‘what?’. So, shift your efforts to emphasize diagnostic discovery and exploration capabilities.
  10. What is your data worth?  Are you sitting on the proverbial goldmine with your information? Would outside organizations (internal or external to your BI-dollar-signcompany) pay good money to gain access to your proprietary data? Or, as some large retailers do, can you use it to add value for your customers or vendors? Take a step back and see the forest – think creatively about all the ways you could monetize the data you already own.

 

#Analytics

#BusinessAnalytics

#BusinessIntelligence

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What’s next for #CPG #CategoryManagement?

What do Walmart, Facebook, Yahoo, Twitter, IBM, Google, EBay, Teradata, LinkedIn, Hulu, The New York Times, MicroStrategy, and P&G have in common? They are all harnessing the power of Hadoop to store, serve, slice, and rationalize Big Data to advance their business. To peer into volumes of data like never before. Volumes of data that have been too big to be this nimble and uncovering things about their customers that they never dreamed possible – until today.

The biggest downside to standard data warehousing and BI tools today is that you have to know the questions you want to ask ahead of time. This creates a never ending search for patterns, outliers, and relationships in your data. If you dream up a question your existing architecture doesn’t support, you have to involve IT or software vendors and re-architect the whole data warehouse.

What if you could gaze into a magic 8-ball and it would tell you everything you needed to know about your retail category – all of the SKU changes to maximize sales,  your out-of-stocks and phantom inventory, your sales by geography or store traits, plus patterns in your data that you did not even know to look for. Welcome to the next generation of BI data warehousing in retail category management – Hadoop!

Why Hadoop?

  • Hadoop is powering today’s Big Data initiatives and is gaining more and more acceptance across many different business units. Coupled with Hive, Pig, Scoop, MapReduce, and numerous others, there are multiple robust ways to attack and slice your data.
  • Your original data formats are unchanged, so you can reuse them in their raw form at a later date. This guarantees no data loss in case you think of some way to explore your data in the future that you have not thought of today. It also does not lock you into a proprietary third party data format.
  • No ETL is required. Data is loaded into the HDFS and then you are done. Then use coupled tools to go unearth the data you are looking for rather than churning it into a cookie cutter format that you hope will give you insights.
  • Hadoop is scalable using inexpensive hardware. Add nodes to your cluster all day long, using junker PCs you have lying around in the closet. No longer do you need a $50K RAID SAN to house and protect your data. Running out of space after 5 years of category data? Just load up some more nodes and you will be good for another few years.
  • Hadoop couples with several analytics vendors – MicroStrategy, Pentaho, Zoomdata, SSRS, Tableau, SAS, with other open source products as well as numerous several built-in packages.

We are breaking new ground focusing on implementing Retaillink or other Demand Signal data in a Hadoop cluster, and applying several analytics packages on top of that to let this new Big Data platform shine in the category management space like never before.

#CPG

#CategoryManagement