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This is yet another question that I get from all angles, partners, customers but even colleagues. BW has been the spearhead SAP application to run on HANA. Actually, it is also one of the top drivers for HANA revenue. We've created the picture in figure 1 to describe - on a high level - what has happened. I believe that this not only tells a story on BW's evolution but underlines the overall HANA strategy of becoming not only a super-fast DBMS but an overall, compelling and powerful platform.


Fig. 1: High level comparison between a classic BW and the two versions of BW-on-HANA. Here as PPT.


Classic BW

Classic BW (7.3ff) follows the classic architecture with a central DBMS server with one or more application servers attached. The latter communicate with the DBMS in SQL via the DBSL layer. Features and functions of BW - the red boxes in the left-most picture of fig. 1 - are (mostly) implemented in ABAP on the application server.


BW 7.3 on HANA

At SAPPHIRE Madrid in November 2011, BW 7.3 was the first version to be released on HANA as a DBMS. There, the focus was (a) to enable HANA as a DBMS underneath BW and (b) to provide a few dedicated and extremely valuable performance improvements by pushing the run-time of certain BW features to the HANA server. The latter is shown in the centre of fig. 1 by moving some of the red boxes from the application server into the HANA server. As the BW features and functions are still parameterised, defined, orchestrated from within the BW code in application server, they are still represented as striped boxes in the application server. Actually, customers and their users do not note a difference in usage other than better performance. Examples are: faster query processing, planning performance (PAK), DSO activation. Frequently, these features have been implemented in HANA using specialised HANA engines (most prominently the calculation and planning engines) or libraries that go well beyond a SQL scope. The latter are core components of the HANA platform and are accessed via proprietary, optimised protocols.


BW 7.4 on HANA

The next step in the evolution of BW has been the 7.4 release on HANA. Beyond additional functions being pushed down into HANA, there has been a number of features (pictured as dark blue boxes in fig. 1) that extent the classic BW scope and allow to do things that were not possible before. The HANA analytic process (e.g. using PAL or R) and the reworked modeling environment with new Eclpise-based UIs that smoothly integrate with (native) HANA modeling UIs andconcepts leading also to a reduced set of infoprovider types that are necessary to create the data warehouse. Especially the latter have triggered comments like

  • "This is not BW."
  • "Unbelievable but BW has been completely renewed."
  • "7.4 doesn't do justice to the product! You should have given it a different name!"

It is especially those dark blue boxes that surprise many, both inside and outside SAP. It is the essence that makes dual approaches, like within the HANA EDW, possible, which, in turn, leads to a simplified environment for a customer.

 

This blog has been cross-published here. You can follow me on Twitter via @tfxz.

The all new SAP HANA Marketplace was unveiled recently with its consumer-grade online shopping experience and capabilities. The new site features intuitive navigation, search & filter, product comparison capabilities as well as a responsive website for mobile devices.

 

Another key feature unveiled in this version is for product owners at SAP and its partner companies, including the innovative SAP HANA startups, to publish their products and manage their own store fronts. As HANA Marketplace is gaining momentum, we are receiving an increasing number of inquiries from the product teams for listing their products on the SAP HANA Marketplace and seeking guidance for providing best online experience for customers.

 

Find below a list of Top 5 best practices that the HANA Marketplace team has put together to help product owners tap into new sets of customers globally effectively:

  1. Offer Free trials
    • Free trials are the most popular offers on the HANA Marketplace. It is important for prospective customers to test drive the solution before making a financial commitment. Example – SAP Customer Engagement Intelligence (CEI) at  http://marketplace.saphana.com/p/3525
  2. Offer Subscription pricing
    • Ideally month-to-month pricing and ability to cancel at any time, think about a price point that is in range with a credit card limit. Example – Decisions by Liquid Analytics at http://marketplace.saphana.com/p/3546
  3. Offer a Starter Package 
    • Prospective customers usually want to start small and ‘kick the tires’ before making a large financial commitment. Think about a price point which will require minimal approvals and reduces barriers to decision making. Example – SAP Sales and Operations Planning (S&OP) Starter Edition at  http://marketplace.saphana.com/p/3555
  4. Make Comprehensive Collateral Available Online
    • Include datasheets, brochures, FAQ, demo videos, customer testimonials….anything to make customer more knowledgeable about your product via e-learning with the aim of eliminating classroom trainings and support calls. Example - SAP HANA App Services offering of the SAP HANA Cloud Platform at http://marketplace.saphana.com/p/1808
  5. Offer Immediate Purchase and Deployment
    • Customers want instant gratification today. Have a “Buy Now” call-to-action rather than “Contact Us”. Also, make the software available for immediate download and provision the hardware immediately in the cloud. The products should ideally have wizard-based configuration and in-app support capabilities. Example – SAP HANA Cloud Platform Starter Edition http://marketplace.saphana.com/p/1805

 

Related Links:

New technologies and enterprise solutions for marketing seem to emerge every day.  How can you find the right one? This infographic will help.  Put on your Sherlock hat and start searching!

 

STEP 1 Observe Your Surroundings

One of the best ways to find the right IT solution is to ask your users what they are looking for.  In case of marketing, simply ask your marketing team a question - what objectives they are trying to accomplish with the new technology?

 

Chances are they will tell you that identifying target audience and engaging with customers deeply are two of their most pressing objectives.  Why? Because the rules of engagement have changed – the customers today are in charge more than ever. They are digitally connected, socially networked and better informed. In fact, according to Customer Executive Board as many as 57% of B2B customers now make their buying decision before you are even aware of the opportunity[1].

 

STEP 2  Gather Your Facts

How can you help the marketing team to engage with prospects before they make their buying decision? You know that potential customers reveal their needs and wants trough web site interactions, social media conversations, prior purchases, etc., in other words, by leaving a trail of BIG DATA.

Your marketing team will need a solution that could analyze the data in real-time and will tell them what customers want so that marketing can:

  • Segment and target the right people at the right time with the right offers
  • Invest the right resources in the right customers, products, channels
  • Enhance customer engagement and loyalty.

 

STEP 3 Draw Your Conclusion.

Test SAP Customer Engagement Intelligence powered by SAP HANA today. It brings together the data to deliver the insights your sales and marketing teams need for compelling engagements with customers and prospects. Tools for customer analytics, contact intelligence, and customer segmentation and targeting can help these professionals execute your business strategies more effectively.  Start your 3-day free trial today.

 

 

 

 


[1] Source – Customer Executive Board @ http://www.executiveboard.com/exbd-resources/content/digital-evolution/index.html

Lots of people think of those questions in terms of black/white, good/bad, legacy/new. As in many, many situations in software and real life, it usually is a trade-off decision. This blog attempts to clarify the differences in both approaches. Ideally, this leads to a less ideological and biased but factual discussion of the topic. Furthermore it should become apparent that the HANA EDW approach allows to work along both approaches within the same (HANA) system. So it is not the case to have - for example - one data warehouse system based on BW (managed approach) and a second, purely SQL-based (freestyle approach) data warehouse system on an RDBMS.


Fig. 1: Two different approaches: managed vs freestyle data warehousing.


Fig. 1 pictures the two different approaches:

  • On the left-hand side, jigsaw pieces represent various tools that are harmonised, meaning that their concepts / objects "know" each other and have the same lifecycle. For instance, when a data source(as an example of such an object) gets changed then the related data transformations (further examples of such objects), cubes, views, queries, ... (i.e. other objects) can be automatically identified, in the best case even automatically, adjusted or at least brought to the attention of an administrator so that the necessary adjustments can be manually triggered.
    Another example is BW's request concept which manages consistency not only within the data warehousing (data management) layers but is also used in the analysis layer for consistent reporting. It's a concept that spans many tools and processing units within BW.
    The individual tools to build and maintain such a data warehouse need to understand and be aware of each other. They work of the same repository which allows one consistent view of the meta data that consitutes the organisation of the data warehouse. When one object is changed, all related objects can be easily identified, adjusted and those changes can be consistently bundled, e.g. to apply them in a production system.
    Due to the dependencies, the tools are integrated within one toolset. Therefore, they cannot be replaced individually by best-of-breed tools. That removes some of the flexibility but at the benefit of integration. SAP BW is an example of such an integrated toolset.
  • On the right-hand side, you see similar jigsaw pieces. On purpose, they are more individually shaped and do not fit into each others slots from the very beginning. This represents the situation when a data warehouse is built on a naked RDBMS using best-of-breed tools, potentially from various vendors. Each tool only assumes the presence of the RDBMS and it's capability to process (more or less standard) SQL. Each tool typically comes with its own world of concepts and objects that are then stored in a repository that is managed by that tool. Obviously, various tools are needed to build up a data warehouse, like an ETL tool for tapping into source systems, a programming environment - e.g. - for stored procedures that are used manage data flows and transformations, a tool that monitors data movements, a data modeling tool to build up analytic scenarios etc. Technically, many of those tools simply generate SQL or related code. Frequently, that generated code can be manually adjusted and optimized which provides a lot of freedom. Per se, the tools are not aware of each other. Thus their underlying objects are independent, meaning with independent lifecycles. Changes in one tool need to make it "somehow" to the related objects in the other tools. This "somehow" can be managed by writing code that connects the individual tools or by using a tool that spans the repositories of the individual tools. SAP's Information Steward is an instance of that. This is pictured as "glue" in fig. 1.
    The freedom to more easily pick a tool of your own choice and the options to manually intercept and manipulate SQL provide a lot of flexibility and room to optimise. On the other hand, it pushes a lot more responsibility to the designers or administrators of the data warehouse. It also adds the task of integrating the tools "somehow". Beware that this is an additional task that adds revenue for an implementation partner.


SAP's Product Portfolio and the two Approaches

As can be seen from this discussion, each approach has its merrits; there is no superior approach but each one emphasises certain aspects. This is why SAP offers tooling for both approaches. This is perceived as a redundancy is SAP's portfolio if the existence and the merrits of the two approaches is not understood.


I frequently get the question whether BW will be rebuilt on SAP HANA. Actually, it is philosophical to a certain extent as BW evolves: e.g. today's BW 7.4 on HANA has less ABAP code in comparison to  BW 7.3 on HANA. This can be perceived as BW being rebuilt on HANA if you wish. However, what does not make sense [for SAP] is to kill the approach on the right-hand side of fig. 1 by integrating the "freestyle tools" into a second, highly integrated toolset which mimics the BW approach because that would simply remove the flexibility and freedom that the right-hand approach has. Fig. 2 pictures this.


Fig. 2: It does not make sense to implement two toolsets for the exact same approach.


What is true, however, is that HANA will see a number of Data Warehousing Services arising over time. They already do exist to some extent as they surged when BW was brought on to HANA. They can be generalised to be usable in a generic, non-BW case. Nearline storage (NLS), extended storage, HANA-based data store objects, a data distribution tool etc are all execellent examples for such services that can be used by BW but also by a freestyle approach.


Finally, I like to stress - again - the advantages of the HANA EDW approach that allows to arbitrarily combine the two approaches pictured in figure 1. You can watch examples (demos) of this here or here.

 

This blog has been cross-published here. You can follow me on Twitter via @tfxz.

We recently conducted a customer webinar focused on how our customers and partners are fundamentally changing their customer interactions using SAP HANA in the high-tech industry. Customers, thought leaders and partners such as ebay, Cisco, and Adobe presented their use cases and success stories on implementing SAP HANA.

 

Below are some of the highlights from the webinar from my live twitter feed @sajal_agarwal:

 

 

 

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1. First #Cisco presented on how @saphana helps its business providing Dynamic Insights for Sales Executives (DISE)

 

 

 

 

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2. #cisco @saphana @SAPhightech high level architecture provides dynamic insights for sales

 

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3. wonderful #testimonials from #cisco customers implement DISE with@saphana @SAPhightech

 

 

 

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4. What happens in an internet minute? @ebay implements @saphana for early signal detection

 

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5. foundation, consolidation and innovation: 3 steps for #ebay early signal detection using @SAPInMemory


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6. Learn @saphana helps #adobe transition to a more personalized and relevant user experience

 

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7. #adobe & its customers achieve tremendous benefits implementing@SAPhightech @SAPInMemory

 

 

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8. Join us for customer roadshow on August 19th with @SAPhightech@SAPInMemory #ebay #adobe #Cisco #idc #intel. Agenda below:

 

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The link to the webinar replay is here.


Look forward to a wonderful physical event in Palo Alto and other remote locations. Will share the details and invitation with you soon!

 

Sajal Agarwal

Twitter: @sajal_agarwal

Weekends, as I noted in an earlier blog, are great for catching up on reading, but so apparently are waiting rooms. Something I recently discovered when I came across an interesting The Economist article in my dentist’s waiting room. By the way weekends are also great for watching sports, like a  IFA World Cup final, which after a very good game and valiant effort by Argentina, Germany finally won. And working for SAP I found it particularly satisfying given that SAP had a role in helping the German team prepare. A while back I wrote a blog “Football (Soccer) Meets Moneyball – Big Data enables wining enterprises” that I commented on a BBC news article discussing how Big Data can be used to shape performance and success, and how SAP is helping a premier football club of lever Big Data. (read it here) SAP is also successfully doing this at the national level as evidenced by the  success of the German national team. In her July 15 blog “Big Data & Spatial Analytics Help Germany Score the World Cup” Marie Goodell does an  excellent job of detailing this. (read it here)

 

But, I digress. So I broken a tooth that required a crown and thus a few visits to my dentist. Ensconced in the waiting room I came across a May 24, 2014, The Economist article “Digital Disruption on the Farm” which talks about how Big Data is helping the world progress in even the most traditional areas such, as  innovating and deriving value in farming. (read it here) In brief, Monsanto has derived a prescriptive planting system they call FieldScripts that provides optimization information on what seeds to plant, where, and how to cultivate each acreage. Basically, predictive analytics for farming. And to use predictive analytics - well you need data – lots of data. From weather history and patterns to soil types and conditions, to seed and other performance data; some publically available some proprietary. So the farmer benefits as they get evidence based advice on what to optimally plant and where given the prevailing conditions. Monsanto benefits, as they not only sell the service, but most likely the seeds, and gain insight into demand on inventory, both of which likely see increased profits and strengthen brand loyalty. However, these are not the only ones who can benefit from Big Data.

 

There are opportunities for everyone in the chain to benefit from Big Data. From suppliers like Monsanto and the farmers to those that make farm  equipment; who can use big data to predict what kind of equipment will be needed for the season and how to equip and deploy it. To those that make fertilizer, irrigation and other products used on the farm to produce the crops; who can they use big data and predictive analysis to see how much of what type of product and material will be in demand for the coming season. Down to transportation and logistics – how much and what kind of transportation equipment will be needed from and to where. Rail and trucking companies looking to optimize loads and routes can benefit from big data. In short everyone in the chain needs to use big data – or they will be left behind as someone else grabs the competitive advantage.

 

One other example of Big Data in agriculture – or agronomics – is John Deere who wanted to go beyond being a manufacturer and become a big data company. They too are looking at innovations in technology and big data to help increase farm yield as well as diversify and drive revenue. There is a  really good June 5, 2014 article in V3 UK here. Quickly John Deere wanted to help its customers enhance productivity, improve crop yield and reduce costs as well as help dealers provide value added services. And John Deere itself wanted to increase its own profitability and drive brand loyalty. They produced a service offering for a growing market by using telemetric data from their farm equipment and agronomic data. They have something that can help them get insight into trends and needs, driving smart inventory and production and they can minimize downtime of machinery in the field by offering preventative maintenance. All the objectives for all three groups above are met by using Big Data. Once again the entire ecosystem around this from parts manufactures to transportation can and must lever big data to stay competitive an succeed. Big Data is a new reality and a necessity for everyone – at least those that do not want to be left behind. Even in the oldest and most traditional of businesses.

 

Take care. And remember to brush your teeth.

 

    • Learn how the SAP HANA Platform for Big Data can help you take a simplified approach to making Big Data work for you in deriving true value from Big Data for your business at www.sap.com/bigdata
    • See how you can leverage data science services from SAP to uncover new signals hidden in your data and drive performance and results for your business at: http://www.sapbigdata.com/services

In discussions with customers on SAP HANA platform often breakthrough innovation and business value take center stage. From an IT perspective also cost and manageability are frequently discussed. The good news is: Now first publications show that implementing and running SAP HANA can provide cost savings even to the IT organization.


Forrester Consulting conducted a cost analysis based on its Total Economic Impact (TEI) methodology to show how implementing SAP HANA could help organizations cut both their IT expenditure and their business overheads. The study provides examples of how much it would cost to implement SAP HANA and how much an organization could save by doing so. Forrester Consulting found that organizations opting to implement SAP HANA could expect to see their software costs fall by more than 70 percent, their hardware costs by 15 percent, and their administration and development costs by 20 percent. Forrester interviewed several customers with multiple years of experience using the SAP HANA platform and conducted a survey of 25 additional SAP HANA platform users. Drawing on the experiences of these customers, as well as own expertise in this area, Forrester constructed a financial model to represent the potential savings associated with using SAP HANA as a replacement for a traditional database platform in several different ways. In this financial analysis, Forrester looked into the impact of using SAP HANA in conjunction with the SAP Business Warehouse (BW), SAP Enterprise Resource Planning (ERP), and a custom-developed application.


The cost savings were realized by reduced hardware and lower software costs, resulting six areas of simplification we have seen as being impacted from how SAP brings in-memory technology into business software: from a simpler data footprint, a simpler system landscape and simpler setup procedures for SAP HANA, as well as from more efficient application development processes and an increased productivity for administrators caused by simpler data processing and operations and a simpler user experience.


To learn more about how to unlock business value and deliver breakthrough Innovation while simplifying your IT and to download the Forrester study and ist executive summary, visit www.sap.com/innovation-and-me.

Oracle finally released their in-memory cache for the Oracle 12c database this week. With it, has already come a good quantity of anti-SAP HANA marketing, with the usual jousting that you would expect between enterprise software vendors. They released a comparison sheet between Oracle and SAP HANA, which is the usual mix of propaganda/marketing.

 

This is compounded because SAP has reseller agreements with Oracle and IBM, so they have to be very careful how they position SAP HANA's capabilities. I don't work for SAP, so I don't have to be careful. Furthermore, I didn't like the Oracle comparison because it's very database-centric, and businesses are application and process-centric. Here's an alternative view on the world.

 

Business

Application

SAP HANA

Oracle 12c

Database in-memory

IBM DB2

BLU

SAP Business SuiteOptimized for SAP HANA - 50% faster on average in response times.Not supportedNo support for BLU acceleration
SAP "S" SuiteSimplified Financials with SAP HANA - 50% less footprint including no totals or separate ledgers. Remainder of SAP Business Suite to follow.Not supportedNot supported
FioriFull support for free Fiori business applications including fact sheets and searchNo fact sheet support; search possible with HANA sidecar databaseNo fact sheet support; search possible with HANA sidecar database
SAP HANA LiveOptimized for SAP HANA, providing real-time operational reports for the Business Suite via virtual data models - no EDW required.Supported with a SAP HANA sidecar databaseSupported with a SAP HANA sidecar database
SAP BW (basic)Full support including full data model acceleration for all business areas including Inventory, complex calculation pushdown (exception aggregation), data load acceleration.Not supportedLimited support for BW InfoCube storage and acceleration
SAP BW (advanced)BW 7.4 is HANA-optimized including simplified LSA++ model, industry solutions e.g. Retail Point of Sale. Support for HybridProviders, CompositeProviders, integration with HANA Information Views.Not supportedNo advanced features
SAP BW Virtual ModelingComplete virtual modeling capability in BW.Not supportedNot supported
SAP BPCSupport for BPC 10.1 Unified Model (based on HANA PAK).Support only for BPC 10.1 Classic ModelSupport only for BPC 10.1 Classic Model
Code AccelerationSubstantial pushdown into the database for complex procedures using ADMPNot supportedNot supported
Data VirtualizationSupport for Smart Data Access data virtualization for Archiving/NLSNot supportedNot supported
Lumira ServerSupport for the Lumira Server analytics platformNot supportedNot supported
In-Memory PlatformHANA is an end-end cloud and on-premise platform with support for database, modeling, graph, predictive, spatial, text, search, integration and application services.Many separate components required for similar functionalityMany separate components required for similar functionality

 

Comparison Notes

 

Note that this is a comparison which is deliberately SAP application-centric. What's important to note is that "not supported" also means in many cases "not possible", in my opinion. For example, the "S" Suite of Simplified Applications is only possible because it's possible to calculate totals and ledgers on the fly. The design of Oracle and IBM's solutions mean that this simply isn't possible.

 

In the projects I'm working on, we find that the sheer number crunching capability of HANA means that we can solve problems we couldn't solve in DB2 or Oracle. For instance, we put together a real-time management dashboard for one company; this was based on 34 separate complex questions that displayed in one dashboard. Using the HANA platform, we could get an end-end page load on an iPad in under 3 seconds based on real-time data. There's no way that this could have been built on DB2 or Oracle - it took 30-40 seconds and that's not an acceptable response time for a mobile app.

 

The other thing that is worth noting is SAP's development direction. I recently spoke to a friend at SAP that put it nicely: "We spent the last 10 years optimizing our products for Oracle and IBM. Now we are spending some time optimizing for our database". Some customers have commented to me that they feel that SAP is investing overly heavily in R&D for HANA, at the expense of other databases, but I don't believe that is a fair assessment: HANA enables capabilities that other databases do not, and SAP is writing software to take advantage of these capabilities. If other databases could do the same things then SAP would enable them (and the software has in most cases been written to take this into account), but they can't do the things that HANA can do.

 

Oracle attacks HANA specifically on the topic of enterprise-readiness, but that's not what we see in the field. In fact HANA is so much easier to configure for High Availability that almost all of my customers use HA/DR scenarios. By contrast, I have almost never come across Oracle RAC, because it's notoriously difficult to set up. And in a recent customer, we had zero issues during user testing on a complex deployment. Not just zero open issues at the end of testing - not a single issue during user testing.

 

Some customers suggest that Oracle and IBM will catch up - but the reverse seems to be true so far. When I last looked at HANA and DB2 a year ago, SAP were around 2 years of development ahead of IBM, but that seems to have increased in the last year - HANA has become much more mature, and IBM haven't made any changes since the release of DB2 10.5. We don't see any SAP on BLU deployments at all or any live customer stories.

 

Final Words

 

This comparison will no doubt be controversial, but it's what we see in the field. I'd welcome feedback, or additional scenarios that aren't in this list. But my conclusion is that SAP are putting all their development efforts to optimizing applications on SAP HANA, and as a customer, you should take advantage of this.

 

Disclosure: I don't work for SAP and received no compensation for this piece, but I have consulted in the past with SAP on various areas of SAP HANA. I'm also a SAP Services Partner with a focus on SAP HANA though I have 16 years of experience with database technologies including Oracle, Microsoft, IBM and others.

Your business department was asking for the SAP HANA platform, your job as IT is the cost efficient implementation and seamless operation. You feel that the business is the clear winner in that game?

 

Think again and imagine what if there are use cases where also your department benefits from the SAP HANA platform.

 

Let me ask you some questions:

  • How often does your company experience IT issues that affect performance or productivity?
  • Would you say that the frequency of such failures impacting your area is: decreasing, staying the same, increasing?
  • How many times does a same/similar failure occur?
  • What is the impact for the business

 

You should continue reading if you think that there might be some room for improvement. And please dont get me wrong, I know you are doing already a great job. But take a couple minutes and think about your current data center operational setup?

 

Count the different hardware and software layers starting from storage, network, server and end-user devices followed by operation system, virtualization, application and service layers oh and dont forget specific facility sensors like, temperature, power usage,.

 

How many different vendor as well as generic management tools do you need for the daily operation?

 

All that is fine and for sure needed, but imagine you could do all this using one platform: SAP HANA? Managing the massive data volumes including structured and unstructured data provided from tones of event, configuration and external data sources daily? Identifying similarities holistically?Performing ad hoc real-time analysis? And predict critical events? Within and allover your data center layers?

 

Data Center Intelligence a data mart extension for IT based on the SAP HANA platform helps you to acquire, analyze and act on massive data volumes from, in between and along any data source in your data center in real-time.

 

  • Maximize IT responsiveness by enabling a holistic view within and allover different hardware and software layers as well as facility sensors to avoid business impacting situations.
  • Mitigate IT risk to ensure business continuity by proving transparency on device connectivity in real-time to detect threats or predict outages.
  • Optimize IT operations to drive cost-efficiency by acquiring, managing and acting on massive volumes of data to optimize resource and capacity management.

 

Identify similarities, perform ad hoc real-time analytics and prevent critical events causing business impacting situations.

 

You are interested? We currently start a co-innovation project for a limited number of customers. Take the chance and work close together with the SAP HANA development teams and SAP own IT departments.

 

You like to know more? Contact us to set-up a first informal briefing meeting and decide afterwards if and how to contribute to the co-innovation project to put ALL your logs into business action.

 

We're looking forward to get in co-innovation with you.

My colleague, Timo Elliott, likes to joke that a data scientist is a business analyst from Silicon Valley.   At SAP, I think our data scientists combine science (e.g. statistics, mathematical models, computer programming) with analytic artistry (e.g. predictive analytics and visualization) to explain the story that the data is telling us.

Data Science in Action -- An Example

Imagine that you are a retail store that wants to invest in a promotion.  To be successful, you want to understand how your customers will behave if you change the price. On one hand, you want to maximize revenue (sales from goods sold); on the other hand, you want to maximize profits (amount that exceeds the costs and taxes of the product).  If you drop the price enough, you'll increase revenue.  But at a certain point, you begin to lose profit.  So your goal is to be able to predict the highest price to charge for your product to gain the maximum profit.

 

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You can use your "gut-feel" to set the price in the promotion.  Or you can base your decision on scientific analysis.  Working with a data scientist, you can create mathematical models that can analyze large volumes of historic point-of-sale data against a variety of variables such as target market, channel, season, competitor prices, and customer sentiment.

 

As these pricing models crunch through the Big Data, they begin to display trends that can better forecast how customers will respond to price changes.  A variety of pricing strategies can be visualized through analytic tools enabling you to:

 

  • Assess revenue / profit trade-offs based on customer demand
  • Optimize promotions (e.g. price, duration, timing) across target markets and channels.

 

With data science, you move from analyzing what happened in the past to predicting what will happen in the future.  In addition, you can optimize your pricing and promotional strategies to best meet your financial needs and improve customer satisfaction.

 

Data Science in Action -- Learn more


If you would like to discover other use cases (in retail, CPG, transportation, media, energy, and more), than join me on Monday, July 21st as I interview Dr. Helmut Linde, Head of Data Science Solutions at SAP.

 

 

In this webcast (part of the on-going SAP Big Data, Big Thinking Webinar Series), we'll explore how data science can help you move beyond traditional analytics to help you discover trends, predict outcomes, and optimize your business - enabling you to become more competitive and efficient.

 

 

Register for the live session:

Date: July 21st

Time: 4pm CET / 3pm UK / 7am PT

Or join us at your leisure by viewing the on-demand version after the broadcast!   Hope to see you there!   ~ Marie

 

About the author:  Marie Goodell is a Strategic Big Data Marketing lead at SAP.  Follow her on twitter @mhgoodell.

Textile Rubber and Chemical Company(TRCC) is debunking the myth that SAP HANA is not ready for transactions and analytics together. TRCC, an SAP® mid-market customer, is a privately-owned textile and chemical manufacturer who is a winner in the Trailblazer Innovator Category of the first SAP HANA Innovation Award.  They are a great example for the industry that companies of all sizes can capitalize on HANA’s speed, agility and effectiveness for transacting on and analyzing data.

 

TRCC implemented SAP Business Suite powered by HANA to replace their lengthy manual reporting processes using 22 independent Sage system databases facing end of life and multiple third-party products. In order to deliver an agile Business Intelligence (BI) environment that provides on-demand and real-time access to financial, operational and sales information at the detailed level, TRCC chose to implement the HANA Live feature of SAP Business Suite on HANA rather than costly and “stale data”  traditional data warehousing alternatives. They also turned to the expertise of Decision First Technologies™ (DFT), an SAP Gold Partner and recognized authority in the BI industry, to implement HANA Live best practices and lay out the roadmap for a successful BI environment.

 

Their resulting solution provides one source for all data and they do not require separate transactional and reporting databases.  This means that there is no delay in providing analytics for management; decisions are now made in real-time on real-time information, no matter how large their database grows.


What makes this story so amazing is that within 2 weeks of implementing the executive dashboard of HANA Live, TRCC found an operational inefficiency in one of their product lines which they were able to correct, saving the company thousands of dollars a day and producing an immediate ROI for the project. You can read the full case study by going to the following link:  http://info.decisionfirst.com/HANA-Site_TRCC.html

 

 

 

Share TRCC innovation award entry on twitter

I am glad to have had the opportunity to join the exciting “SAP HANA Business Application Contest” event at SAP Forum in Shanghai, China.  After two-months of preparation, seven customer and partner teams were selected to present their HANA applications on the stage competing for five awards.  Their presentations were each judged by a strong committee of six judges: two SAP VPs, two customer CIOs, one Intel director, and one VP from analyst/media company. The judges shared positive feedback and had valuable discussions with the presenters. This two-hour event was filled with a curious and engaging crowd.

 

Mark Gibbs, President of SAP Greater China, said: “We place great importance on growing and expanding the SAP HANA ecosystem. The success of the SAP HANA Business Application Contest demonstrates the openness of the SAP HANA platform and how it generates business value. We intend to leverage the collective power of our ecosystem to drive more innovation and unlock the potential of the SAP HANA platform. SAP will continue to co-innovate with our customers and partners to bring more customized applications to the SAP HANA platform.”


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Five outstanding teams from Nippon, Yunnan Hongxiang, AdMaster, Kintiger Co., and Zoomlion Co., demonstrated strong scenarios and won the following awards:

 

Best Business Application Award: Nippon China used SAP HANA technology to expand their iColor website by collaborating with Hadoop to create a seamlessly integrated personalized color recommendation solution. SAP HANA's high-speed memory and in-depth analysis of unstructured data helps to recommend the color choice to improve user experience and provides deeper business insight. The following photo shows Ken Tsai, VP, head of HANA and Data Management Marketing, presenting the award to the winning team.

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Best Business Value Award: AdMaster Technology team used SAP HANA to build a SaaS platform that provides customized analysis for personalized social counseling to customers in different industries. With SAP HANA’s analytical computing power and massive comprehensive text analytics, AdMaster was able to easily achieve real-time text data queries, sentiment analysis, entity extraction, and semantic analysis. Through data visualization, customers can quickly see the most intuitive and valuable results of data analysis.  Moreover, SAP HANA text analytics allows us to deal with international expansion without changing the structure.

 

Best Innovation Pioneer Award: Based on the SAP HANA platform, Yunnan Hongxiang technology team built an application that balances the inventory across different stores within a region.  It is comprised of the traditional corporate level macro-inventory allocation system and establishes a micro-balanced circle among retail stores to achieve a more proactive, targeted and timely allocation. This solution is great in planning and achieving optimization through real-time inventory data replication in SAP HANA.  It leverages the in-memory computing capabilities and predictive analysis algorithms to design an accurate micro level demand forecasting and dispatching route optimization. This effectively reduces the cost of cross-shop and helps enterprises respond to changes in inventory and procurement needs in a timely manner.

 

Best HANA Feature Use Award: Hangzhou Kintiger team built a SAP HANA solution for Century Sunshine Paper Co. to accelerate their monthly financial closing process with a BI platform. This solution uses SLT to synchronize SAP ERP data into HANA in real-time to accelerate key calculation models. The results are smaller amounts of data which is written back into SAP ERP to continue the business workflow. This solution implements financial closing algorithms within SAP HANA which significantly increases the calculation speed and makes the BI run more smoothly, efficiently, and accurately, bringing significant economic benefits.

 

Most Promising Application Award: Zoomlion Technology team uses SAP HANA to build a corporate level BI platform that covers all factory management, sales management, and service management teams. This is a typical business BI system that leverages the efficient data analysis capabilities and real-time data processing capabilities with unprecedented speed to process a large number of non-integrated, structured and unstructured data on SAP HANA. This allows companies to make real-time decisions and change the traditional management style. Businesses can create a data-driven business model and helps company to release new business insight. This allows companies to make real-time decisions and create a data-driven business model that changes traditional management.


All application details can be viewed in SAP HANA Business Application Contest website, including one project description page with one video link in Chinese.

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In June, my husband and I had a delightful holiday in Germany visiting close friends. We had the privilege of watching the German National football team play in the 2014 FIFA World Cup from people's homes and in public viewing stands along the Rhine. We missed the Germany / USA game because we were on a flight home, but when we got back to San Francisco, we continued to watch each game at home on our big TV screen. What amazed me about the entire World Cup is how the Germany National Football team kept it simple and stayed focused. Congratulations to the German National Team!

 

How Big Data Helped the German National Football Team Train

Aside from great talent, exceptional teamwork, and dedicated training, the team took advantage of Big Data.  Working in collaboration with the German Football Association (DFB) and SAP, the team used SAP Match Insights based on SAP HANA technology. SAP Match Insights helped the team analyze matches by processing vast amount of data to help players improve their performance. Video data was captured from 8 on-field cameras and crunched into thousands of data points per second.  This enabled coaches to analyze performance metrics, such as player speed, position and possession time.  Coaches could then provide feedback to players via mobile devices to help them improve their game. Two recent press articles ("Germany's World Cup Tactics: Shaped by Data", The Telegraph and "Germany's 12th Man at the World Cup: Big Data", CIO) describes in detail how the solution works.

 

 

 

See How SAP Match Insights Works

If you happen to be at the Esri User Conference in San Diego this week, we'll be highlighting SAP Match Insights at our demo at this amazing spatial conference.  If not, check out some of these YouTube videos to see it in action and hear what others think about it:

 

 


It's exciting to see how Big Data -- including spatial analytics -- is becoming more main stream, enabling all of us to take advantage of "location" to run better.

 

Spatial Analytics Can Help Any Team, Business, or Organization

Today, the Esri User Conference, SAP announced new spatial capabilities across SAP HANA, analytics, mobile, and business applications to help break down the silos between GIS and business data -- enabling you to uncover new location-based insights and accelerate decision making.

 

 

SAP HANA is able to consume, process, and analyze transaction, spatial, and text data within one unified platform -- enabling organizations to analyze location-based, Big Data to better understand what happened and predict future outcomes. With new support for Esri Query Layers, business users can now run complex spatial queries on massive volumes of data in SAP HANA without having to move data between systems. In addition, SAP HANA integrates with Esri geospatial services and content to enable business users to gain value from location intelligence.  Developers can quickly develop high-performance spatial applications to help uncover new insights and accelerate decision making.

 

 

SAP Lumira has been enhanced to support geospatial analytics from Esri ArcGIS Online for agile innovation, enabling users to visualize data on a map to see new patterns and trends.  Check out how SAP Lumira was used analyze and predict the outcome of several games in the 2014 World Cup series!


In addition, SAP is now delivering spatial analytics to SAP Business Suite applications  through a GEO.e framework delivered by SAP Consulting.  As a result, business users and field workers can now visual business data about land parcels, buildings and work orders on maps from within SAP applications, such as  SAP Work Manager powered by the SAP Mobile Platform. To view these new innovations, stop by our booth at the Esri User Conference --- and discover how your organization can win big with Big Data.

 

About the author:  Marie Goodell is a Strategic Marketing Lead for Big Data at SAP.  Follow her on twitter at @mhgoodell (#SAP #BigData)

As you expand your system landscape to better address your business needs you are faced with a recurring question: make or buy needed extensions? SAP users in today’s Environment can create some exciting and innovative applications by leveraging the power of SAP HANA and their existing ABAP skills. As part of the 2014 SAP Middleware webcast series the upcoming webinar will give you insight on how to customize your on-premise and cloud system landscape with technology available in SAP’s development portfolio.

 

Attend this webinar to learn:

 

• How to use SAP development environments to extend your SAP systems

• How to make the most of SAP HANA Native Development

• How to re-use your investments and skills with ABAP on SAP HANA, thereby combining the best of two worlds

 

Date: Wednesday, July 16, 2014

 

Time: 11:00 am ET | 15:00 pm UK | 16:00 pm Central Europe

 

Featured Presenters:

Dr. Wolfgang Weiss, Director Product Management for SAP HANA Platform Extensions, SAP
Helmut Grimm, Head of MEE Global Centre of Excellence for Middleware, SAP

Duration
: 60 minutes

Register HERE for the live event and to get the recording.

Over the course of my last few blogs I have discussed and looked at how SAP HANA interacts with the Hadoop the Big Data world. Needless to say I was very excited when Databricks announced its partnership with SAP on July 1’st. You can read the Databricks press release here. This completes the trilogy – as SAP HANA now supports all three approaches to SQL on Hadoop - batch scale, disk optimized and now Spark in-memory. This means that SAP is able to work with Hadoop and NoSQL and meet the varied needs of customers as they adopt and begin to utilize these technologies in their data fabric. Integration with Hadoop just got better. And this is great news for SAP and Hadoop. Databricks has created a Spark distribution, based on Apache Spark 1.0, integrated with the SAP HANA. You can download it here


Someone at the recent Hadoop Summit North America show asked me if I felt that in-memory on Hadoop was a threat to SAP and SAP HANA. My response then, as now, is no it is not a threat it is a complimentary piece of the puzzle that makes things better. There are times when you must move your data around and times when you will want to access it in situ – and SAP HANA’s smart data access let’s you do just that. The only down side is the latency of the target system. You get instant results and speed from SAP HANA, but if the results include data residing in another system the query will be only as fast as the response from other system. Now with Spark providing in-memory for HDFS and NoSQL the responses back from the Hadoop systems will be faster. Less latency is better performance overall. The faster the response the more HANA’s smart data access will be used to join data optimally stored across the data fabric. The follow up question was, but will in-memory Hadoop not replace or mitigate the need for HANA. To which I noted no – they cannot. Would you really put your vital, mission critical data in Hadoop, which at this point, does not offer ACID (Atomicity, Consistency, Isolation, Durability) based persistence to guarantee that database transactions are processed reliably. The Hadoop community may be working toward this but it is a long way off. Hadoop is a great place to store contextual data that can be combined with enterprise data to enrich it, and now Spark can provide faster access to that data. Besides SAP HANA is much more than just an in-memory data store – it is a platform providing an application server, web server, powerful libraries and processing engines, all where the data resides. So I see in-memory Hadoop as complimentary and enabling not a threat.


There is great power in bringing the compute to the data, rather than doing it the other way around; this is why SAP HANA was conceived and built. And in the evolving IT landscape that is an optimized data fabric that needs to woven together SAP HANA’s smart data access can help achieve this. The integration of SAP HANA and Spark provides a simpler process for developers and data scientists to start from a single system integrate data stored throughout the data fabric and bring the result sets back. SAP HANA provides Spark developers rich analytics capabilities that do not currently exist in Spark, (Text Analytics, OLAP, Geospatial, OLTP) and they can use HANA to do all the compute and return the results (not move the data) to Spark. As well they get access to the apps that are built on SAP HANA and use its smart access capability to access data in situ on a variety of data stores in the data fabric. This integration now means that those developing on SAP HANA can now enrich enterprise apps and analytics with insights derived from contextual data that store on HDFS and NoSQL systems; along with data in other data stores. And keeping with the open agnostic SAP approach that I have discussed and expounded previously – the Spark integration accessing HDFS can work with any Hadoop distribution so SAP continues to be agnostic and open around Hadoop. Though as I have often pointed out before we do have a reseller agreement with Hortonworks.

 

This integration is a beautify synergy and a nice step forward as we weave together the data fabric of your enterprise.

 

  • Learn more about SAP HANA's smart data access capability here.
  • SAP HANA Platform for Big Data can help you take a simplified approach to making data work for you along with Hadoop. Learn more about how you can derive true value from Big Data for your business at: www.sap.com/bigdata.
  • Download the Spark distribution integrated with SAP HANA platform (based on Apache Spark 1.0) Here

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