#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





Getting Started with #BigDataAsAService #CPGMarketing

Good Saturday morning. Enjoy your coffee and dive a little deeper into an article I recently found.

Written by Raghu Sowmyanarayanan, a vice president at Accenture, he spells out the major thoughts around what the newest trends in big data for enterprises.

Big-Data-as-a-Service (BDaaS) is an emerging trend with great potential for adoption. We have begun to hear CxOs say that BDaaS makes big data projects viable. We explain why the technology is so appealing.

Mr. Sowmyanarayanan covers these topics in his article and the link to the entire piece is below.

  • What is BDaaS?
  • Is the BDaaS Architecture Rigid?
  • Why BDaaS?
  • Top 3 Myths about Big Data as a Service
  • Myth #1: It is an Infrastructure Play
  • Myth #2: Architecture is Very Complex
  • Myth #3: It is Hard to Implement

Source:  Getting Started with Big-Data-as-a-Service





You are your password: How #MobileIdentity management hopes to replace your first dog’s name

“Mother’s maiden name”
“Name of your first pet”
“Favorite restaurant”

Those are but a few of the security questions or reminders that help us keep track of passwords across multiple sites and applications. Online service, like Evernote, that sync across multiple devices have stored countless username/password combinations to keep our digital society moving.

However, passwords will be long forgotten – rather than temporarily so – by the end of the decade, said one tech exec who is pushing for a new approach to passwords.

Hugh Owen, vice president of product marketing at MicroStrategy, said, “[Mobile identity management] is going to be very mainstream in a very short period of time. It will be interesting how long it is – maybe four years, five years – before we look back and remember upon the time where we used to rely on passwords and had to remember them all.”

His company is helping to push mobile identity management through wearables, what many security experts hope is the magic bullet for the long outdated mother’s maiden name, “123456” or string of random characters scrawled on a sticky note. Mobile identity management is any service that makes use of pre-verified mobile devices, like smartphones or smartwatches, to send authentication keys, temporary tokens or expiring passwords to provide access to some secure system.

Research increasingly shows traditional authentication hurdles are easily duped and more trouble than they’re worth, and enterprises would do well to look for alternatives both internally and client-facing.

Last month hackers used background information amassed from different cyberattacks and social engineering efforts to dupe the “Get Transcript” application on, siphoning nearly $50 million in illegally requested tax returns in the process. Take that into account with the research Google released in May that shows traditional authentication means do not even help users – only 60 percent of users remembered the answers to questions like “What is your favorite food?” – and make it more likely for cyber criminals to correctly guess questions with popular answers. Some people think mobile identity management could be the answer in the enterprise.

For that reason, MicroStrategy continues to develop its mobile identity management app Usher, a version of which launched with the Apple Watch. Owen said that the idea is nothing new, but it will be the heavy adoption of wearables – which 451 Research contends is already underway with the release of the Apple Watch – that will help take the complex back-end process of identity management and simplify it to a few taps of a smartwatch face.

With Usher’s newest features, organizations can use an Apple Watch to access office locations, devices, business systems and more, and validate identities and discover nearby users. Owen said the new Apple Watch capabilities are more conducive to the at-a-glance workflows of the average user, and he’s always impressed by the creative ways client’s utilize Usher’s software development kits to extend the platform to functions they need.

“We’ve seen some really interesting implementations of it in terms of banking where people are using Usher as the method of second-factor authentication for both giving people access to systems and also approving transactions. It’s integrated in such a way that it’s just part of the workflow,” Owen said.

He also mentioned some programs the company set up at the Saudi Arabia Ministry of Foreign Affairs and Georgetown University, the latter of which is conducting an ongoing “smart campus” pilot that allows students access to buildings and online accounts through the app as opposed to a physical key card.

Some competitors, namely oneID and Authy, also seek to attract an enterprise audience, but MicroStrategy seems to be gaining notable traction. For instance, Apple specifically mentioned its partnership with MicroStrategy’s enterprise efforts in its most recent earnings call, a rare name drop for the normally taciturn Cupertino company.

For the enterprise, mobile identity management seems like a no-brainer. The technology is there; all that’s needed is the implementation. This could be the killer use case that brings smartwatches out of the C-suite and into the hands (on to the wrists?) of the average user.


Source:  You are your password: How mobile identity management hopes to replace your first dog’s name


#BigData – All of the Hype – None of the Calories!

There has been a lot of hype in the IT industry around Big Data over the last year. It’s been quite breathtaking watching the polarization that has come with this hype, and I have found that everyone falls into one of three camps. When you are reading or listening to some rhetoric about big data, it helps me to classify the argument into one of these three camps, that way I can discern what I am hearing or reading more quickly.

Camp #1 – They are selling something else. So, company A has a mobile app that collects data from a MSSQL server in the cloud, handles maybe 500 GB of data, and they don’t really have a clue what big data is all about. But, everyone is talking about big data, so they want to get into the game. They use phrases like “We’ve always been about big data” or  “We’ve been doing big data for 20 years”, or “We go from big data to smart data”. I’m sure they have a great mobile app, or they have a really clever data model in Teradata – but I generally see these as red flags as NoBigData. No big deal. Maybe the convolution they are creating around big data is generating some big sales for them. I don’t know. Big data sounds cool, right? Surely everyone does big data? If you find the conversation about big data quickly devolves to the cool user interface, or real time data collection via a mobile app, chances are they are just selling something else. I don’t have a problem with non big data products. Not everything should be a big data project to be completely honest. Just don’t call your product big data when it isn’t. It’s ok, really. My car or my DVD player aren’t big data either, but I use them regularly.

Camp #2 – They’ve been ordered to implement big data. These are the teams that know they have a mobile cloud app or a clever DB2 data warehouse, but the CIO has given the mandate that” everyone is doing big data, and so shall we all”. These folks would rather have their arm caught in a wood chipper than feed the big data hype, and they will do everything in their power to kill the initiative without sounding like an obstruction. Generally, I see these folks as hardened IT folks who have made their careers on another database platform, are comfortable with it, heck may even love it. It’s like asking them to cheat on their significant others with someone they don’t like. If it ain’t broke, why replace it? You see these teams, trying to install Hadoop on a TI-85 calculator, and then loading 5 TBs of data, and then complaining the query took an hour, so big data is busted. Maybe. Probably not. I bet they didn’t read the manual, because, you know – that’s against the code….wink wink.

Camp #3 – They get it. To be fair, some of these concepts require a completely new understanding on how data works. Schema on read, for instance. This just boggles the traditional RDBMS developers mind. Typically, you look at your data, create a table, set it’s column data types (these columns are integers, these other columns are strings), then load the data, and then output it to a report. This is called schema on write. I define the table, when I write the table structure. With Hadoop, We load the data, then figure out which columns are integers or strings, and then output the data to a report. This is called schema on read. Why is this significant? I can change the entire data model in 5 minutes. That is not very easy in Oracle or MSSQL. If I built an entire reporting application, and realized a year down the road that what I thought was an integer was supposed to be a character, I can still fix that in 5 minutes on a Hadoop platform. It would take longer than that to put together a project plan to do that in Oracle. I can also add a column to the end of my table, and then figure out what to do with it 6 months later. These concepts are so far removed from traditional databases that they just do not compute. But, when you see someone truly understand what these new super powers bring, then you can see the excitement. Speed, scalability, agility, cost savings – every single one of those are worth a consideration. Maybe when you put all four together in the same sentence, people just assume they are too good to be true?




#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





#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.






#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.





#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





#CPGMarketing: The Age of #DataObsession

This new era of big data (some say huge data) is being called “The Age of Data Obsession.” Below are a few snippets from the recent Sogeti / Ovum Business Intelligence & Information Management Symposium 2015.

  • Information is a fundamental currency of business created from the raw material of data, and while in recent years that resource has become abundant almost beyond belief, our ability to benefit from this insight has lagged behind. Organizations must therefore scale up their information factory, accelerate their business processes, and become obsessive about applying data to all aspects of their decision-making, or risk becoming noncompetitive and irrelevant in the modern data-driven era.

This is clearly a call to action or fall behind and out of the game.

  • For best-in-class businesses, the obsession with data entails its application to every aspect of their operations, from the optimization of business processes, through to decision support for more complex strategic problems. It involves interrogating as wide a range of sources as possible, both internal and external, structured and unstructured; and of delivering the resulting insight at a speed which can match and ultimately accelerate those operational and decision-making processes. Increasingly this requires real-time or near real-time data analysis and presentation, which has significant implications for the data to insight process.
  • Manipulating data at this speed and scale requires a fundamental change in approach, both in terms of technology, and of the underlying data management processes that are applied. From a platform perspective, we are currently seeing the integration of solutions specialized for particular aspects of data handling and manipulation into a unified architecture, reflecting the need to combine existing data warehouse investments with newer big data systems and analytic databases. Logically however, the change in data analysis goes much further, with a growing design mind-set that mandates a large data lake to which organization is applied only at the point of seeking to answer a question (driven in part by the rapid adoption of in-memory computing).

This new obsession blows away the capabilities of traditional relational database management systems (RDBMS) and is tailor-made for what big data (primarily using Hadoop) can achieve. This is true both in the capability to incorporate unstructured data and rapidly load, process and present that data in insightful ways.
Combined with BI analytics tools harnessing the new technology this data brings power to the decision maker.

  • There is a big caveat here though: however powerful the technology, if the organization does not also upgrade its foundational data management processes and its information management strategy to match, then the outcome will at best be indiscriminate and at worst chaotic. From a strategy perspective, organizations must define their information needs and capabilities in support of business objectives, while data management processes must be sufficiently robust so that insight can be generated from data in a systematic and repeatable fashion.

Source: Sogeti / Ovum Business Intelligence & Information Management Symposium 2015




#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