Tag Archives: Data Warehousing

Why Mobile BI becoming the first choice for BI users?

9 Jul

Mobile business intelligence is becoming a leading trend within the BI market. According to Gartner, one-third of all Business Intelligence access will be through mobile devices in the next few years. Over the past several years solution providers have placed a lot of effort into developing interactive mobile applications that can be used by decision makers on the road. Although it has been a slow road to broad adoption, mobile BI is eventually fathering to make encroachments into the general business intelligence market.

It’s tough to refuse the fact that most of us love our mobile phones, tablets and ipads and with technology advancements and widespread adoption of Androids, iPhones, tablets and iPads it is becoming a big tug-of-war within the office to bring business applications like business intelligence, CRM into these mobile devices. Adding to this many organizations are even adopting a ‘BYOD’ (Bring your Own Device) policy to get started as quickly as possible and vendors are able to provide BI offerings that allow companies to provide enhanced analytics and information access.

Expanding Mobile BI market

Speed, power, money, followed by interactive dashboards and parametric reports are the reasons for businesses to deploy mobile BI as a key element of their BI environment. The adoption of iPad and tablets eventually becomes the first choice for BI users. Predicting the potential user centric market many vendors have started their development efforts in expanding the mobile BI by bringing in attractive dashboards, user friendly navigation etc, while organizations too are slowly switching their adoption towards the mobile BI than implementing an in-house solution.

Vendor’s delivery model

Companies like ZSL, expands their mobile BI offerings to meet business needs and offer high level of interactive dashboards and ease of use full spectrum BI applications that provide end users liberty to do proper decision making. Eventually these features and functionality within the mobile environment as similar as web-based or desktop application leverage an alternative solution to the BI users. Consequently organizations will no longer required the option of selecting on-premise BI; they would rather prefer a single solution choice of Mobile BI with more real-time, in-memory and advanced analytical access.

Although it is just the outset of the mobile development, more advanced solutions will be developed constantly to fulfill the growing requirement of the users on the roads. With continued growth in mobile application development and analytics integration, companies can get a complete insight of what is happening within their organization.

Rage on iPads and tablets devices

The increasing rage on iPads and tablets is yet another reason for the users to prefer mobile BI. Users have widened their adoption to iPads and Tablets PCs and vendors to support the increasing demand are developing application that can be easily be integrated with any platform. As the use of tablets and iPads are invariably increasing, BI adoption is more likely to expand exponentially within organizations as usage patterns expand to more employees

Sales Analysis and Visibility for the users

Aside from overall use, sales analysis has always been at the forefront of mobile BI adoption. This provides the basis for more in-depth analysis in relation to customers, suppliers, product movement, and industry. Therefore, sales managers and other users involved in partnering or supply chain management (SCM) will no longer need to download or refer outdated reports henceforth more opportunities in hand and more business relationships providing visibility to their business.

Mobile BI is here to stay, and will continue to grow rapidly, as employers increasingly look to keep managers and decision-makers “on the hook” on a 24×7 basis. In other words, certainly there’s hope — but there’s also hype.

About the Author

Shaughn is an industry analyst for business intelligence. For over ten years, he has assisted clients in business systems analysis, software selection and implementation of enterprise applications. Shaughn is the channel expert for BI for the small and Mid-Market segments at ZSL and conducts research of leading technologies, products and vendors in business intelligence, marketing performance management, master data management, and unstructured data. He can be reached at shaughnk@zslinc.com. And please visit Shaughn’s blog at zslbiservices.wordpress.com



3 Jul

The essence of management is making decisions. Managers are perpetually involved to measure alternatives and make decisions for a wide range of problems. Just like we have different managerial styles, there are different decision-making styles. Decision-making is the heart of strategy deployment. Making decisions involves uncertainty and risk, and decision makers have varying degrees of risk aversion. It must be coherent, relevant and rapidly taken. Decision making also involves qualitative and quantitative analysis and some decision makers prefer one form of analysis over the other. Decision making can be affected not only by rational judgment, but also by non-rational factors such as the personality of the decision maker, peer pressure, the organizational situation, and others.

The most essential raw material when making a decision is your Information. Organizations today have access to almost unlimited amounts of data – sales, demographics, economic trends, competitive data, consumer behavior, efficiency measures, financial calculations, etc. However, many decision makers in organizations feel mazed and bewildered. They have islands of data and still are not capable of making the correct decisions, or understanding where they really are. They fall under the hallucination that mere data is enough. If we have the data and facts, then what more do we need? In today’s connected digital economy, it is very easy to get data yet it is difficult to convert this data into meaningful information for a perfect decision making.

Here are few approaches you can adapt to make better decisions.

  1. Work on the right decision problem. Be careful in stating the problem, and avoid unwarranted assumptions and option-limiting prejudices.
  2. Specify your objectives. Determine what you want to accomplish, and which of your interests, values, concerns, fears, and aspirations are the most relevant.
  3. Create imaginative alternatives. Alternatives represent different courses of action, and your decision can be no better than your best alternative.
  4. Understand the consequences. Determine how well different alternatives satisfy all of your objectives.
  5. Grapple with your tradeoffs. Since objectives frequently conflict with each other, it becomes necessary to choose among less-than-perfect possibilities.
  6. Clarify your uncertainties. Confront uncertainty by judging the likelihood of different outcomes and assessing their possible impacts.
  7. Think hard about your risk tolerance. In order to choose an alternative with an acceptable level of risk, become conscious of how much risk you can tolerate.
  8. Consider linked decisions. Many important decisions are linked over time. The key to making a series of decisions is to isolate and resolve near-term issues while gathering information relevant to issues that will arise later.

To know more on how we have created better decision systems, please talk to Shaughn Knight.

Concept of Social Business Intelligence

18 Jun

Business Intelligence and Data warehousing services have been acquiring greater part of the information technology in the recent years. Although the BI tools and services are quite expensive, still companies required them in order to make right business decisions and remain efficient to provide their customers, clients and members with high quality service. There were key decisions made in organizations every day and executives had to rely exclusively on data-driven systems. These systems were aggregated into Business Intelligence (BI) platforms, showing key data from all of the systems in the organization. As these systems were purely data-driven and therefore backwards looking, they had no ability to incorporate real-time, rich, insightful knowledge – human knowledge. The fact is that data systems simply cannot keep pace with the rapidly changing business landscape. Whether you’re trying to track time-to-market for a product, determining competitor actions, or forecasting sales of a new product, your people have important information and context to share. They talk about it in the cafeteria and in the hallways, but it’s not in your BI systems.

So comes the Social BI

What is Social BI?

Social BI is nothing but the idea that we can consolidate from the social information to make better-informed choices that has imbued our lives. Social BI aims to bring that same power to making better business decisions. To be precise or simple social BI helps you to make right business decision through the socially available information in Wikipedia, facebook, twitter about your product, competitor or services.

Social business intelligence can offer organizations a means of achieving more accurate, and therefore more useful, data. People consistently express personal opinions on a diverse range of subjects via social media sites such as Facebook and Twitter. By monitoring, compiling and analyzing freely-shared thoughts on these sites, firms can gain substantial insight as to how their industries, organizations, products and services are viewed by the public. This information can then be leveraged to improve their offerings.

Business intelligence tools provide organizations with the means of transforming the monumental amounts of data generated on social media channels into a usable format. However, social business intelligence tools are only useful when properly implemented. To improve the quality of that data and their ability to analyze it, many organizations invest in association members’ software containing advanced business intelligence tools. By doing so, a firm can improve its knowledge of the industry and its customers and use that information to become more efficient, more productive and more appealing.

For more information on Social Business Intelligence, contact Shaughn Knight

Challenges you face when trying to implement a BI Solution

11 Jun

Although companies are considering or actively implementing Business Intelligence (BI) technologies, the top management faces numerous challenges in their ability to execute company’s strategy while utilizing their current BI/DW approach. The current economic difficulties are creating even greater interest in BI software because of the potential it offers to analyze data to identify opportunities to cut costs or increase sales. With IT budgets essentially flat this year, Forrester Research still expects BI revenue to increase from $8.5 billion in 2008 to more than $12 billion in revenue in 2014. Large software vendors such as IBM, Microsoft, Oracle and SAP have seized the opportunity by making large BI acquisitions in recent years. Yet many companies have faced challenges with BI, either because they could not find a solution that fit their needs, because they implemented a solution that addressed some needs but left others unfilled, or because the cost and effort associated with implementing a BI solution wasn’t commensurate with the results. This article will attempt to address these concerns. We have listen to many companies facing challenges including

  1. Reports are inconsistent and does not truly reflect the real company information
  2. There are lot of different teams working of lot of different tools and producing a lot of different reports
  3. We have all these reports but now what? It is unclear on what we can do with this information
  4. There is tremendous amount of data collected everyday but there is hardly any data analysis done on that
  5. Disconnect between business and IT users

Also accompanied by them are challenges that have been unlimited over the years, those include:

  1. Disconnect between IT and business users
  2. Change management (Transforming Organization from current state to desired future state)
  3. User adoption
  4. Master Data Management (Defining and managing non-transactional data entities within an organization)
  5. Reactive instead of proactive approach for BI
  6. Lack of Strategy
  7. Security and customization integration
  8. Data Governance (Managing data assets formally throughout the enterprise)

However, there are key challenges that are hurdling to the success of BI & DW implementation:

  1. Expense: It can cost hundreds of thousands of dollars or more and takes months or years to implement a full-scale traditional BI solution. Traditional BI applications require a very time-consuming and usually quite expensive process of defining requirements
  2. Moving Target: BI scope changes more rapidly than in other implementations, especially when the project is coupled to an ERP Business Transformation. These because any change in processes, business or organization influence the final outcome.
  3. Sponsors and user commitment: in many cases users feel challenged by the new technology which changes the way they operate and in addition they have very demanding business cycles (think about Month End Closing Procedure); as a consequence they usually give low priority to the project.
  4. Proper project positioning: “Business” and “Intelligence” are two common words which hide the complexity of the philosophy required implement a multilayer solution and the business transformation always associated with it.

For a Company to properly address these challenges it requires:

  • Good functional/business/technical knowledge in the implementation team. EA experience would be a great benefit
  • Maturity assessment to put in place a reasonable roadmap.
  • Short projects (ideally 6 months) to put in place the BI architecture and a qualified BI department able to tune the solution without jeopardizing the principles.

The best way to do a BI project is to follow a methodology that has proven successful many times over before. The major BI vendors have focused on relatively large and expensive one-size-fits-all approaches that have left many companies searching for a BI solution that fits their needs. The report mining approach to BI provides an inexpensive and flexible approach to deliver validated data to users in the format (Excel) that gives them the ultimate in freedom and flexibility to generate whatever analytics they can conceive to deliver higher revenues and reduce expenses.

For more Information on how ZSL has helped companies to overcome these challenges, please contact Shaughn Kinight

Outsourcing, Off-shoring and Near-shoring – what works or does not work for BI & DWH

14 May

When it comes to Business Intelligence (BI) and Data warehousing (DW) there are always contradictory attributes arising within the industry. One among them is vendor selection. Whether to consider a consultant or go for an outsourcing vendor and if outsourcing, what can be outsourced to onshore, off-shore or near shore?

Most companies have used Data warehouse & Business Intelligence consultants at some point of time – but what about outsourcing? What exactly the companies’ interested in? What works or what does not works for BI and DW projects?

Such questions are certainly expected from various decision makers with respect to the vendor selection till they get a proper solution.

How to select a vendor

Well, the unique selling point of any outsourcing vendor is their customer testimony. The published customer testimonial will show you only an ideal picture of the vendor’s perfection and not the failed projects. Practically failed projects of a vendor are tough to be identified.

Ironically the selection criterion for a suitable vendor becomes very critical. So how do you pick the one that is right for you?

You need to gather answers to some fundamental questions involving availability, security, performance, and customer service. From these information, the best way is to follow high-level, yet restrictive, criteria and only then compare them on a feature-by-feature basis.

  • Meeting your Business Requirements: Be sure to carefully consider your business requirements and go with a vendor that meets them. You may risk going with a smaller vendor, but you are more likely to get the BI deployment you want.
  • Availability: It’s important to understand if the service is deployed on an underlying infrastructure that is backed up with a meaningful service level agreement. The level of availability you need depends on the criticality of the service to your business. Nevertheless you’re looking to move your business intelligence systems to the cloud, it’s likely very important for the cloud service to be highly available. However, for moving secondary application you might not require high availability of the cloud solution. Security: The biggest objection about cloud computing is security, taking corporate information outside the four walls. It should be notable that vendor’s may use the same server to host even your competitors data. Most vendors go about cloud security through the conventional means of various levels of encryption, firewalls, etc. So make sure where is the vendor server that hosts your data center and what is their business continuity during natural disasters? This will give you a satisfactory figure of how your vendor will be able to manage your data in a secured way.
  • Performance: As the cloud services gets matured; companies are expecting performance metrics from the vendors to support the growing business critical systems that make their business run. They expect a better performance than when it was on their own data center. So test your vendors asking how does the cloud service provider define performance? What metrics do they use? How does their definition of performance relate to end user satisfaction?
  • Customer Service: As a company you need to analyze the vendor yourself by
  • How quickly does a vendor return your calls?
  • How open are they in discussing what kind of technology they use or who their providers are and how often they have downtime?
  • What servers they use and the software they run and their disaster recovery plans?

What can be outsourced?

As generic rule, you can outsource anything but what do you want to achieve with outsourcing?
Is it the lower costs? Better service to users? Or both.

When you look at the triple factor Quality, Time and Cost,

  1. Quality and Time ~ Cost Increases
  2. Cost and Quality ~ Time Increases
  3. Time and Cost ~ Quality increases

So quality, time and cost are invariably proportional to each other.

If you ask is it ‘the right choice’ for a company to offshore or even outsource it’s BI projects:

It depends on how much DW work you have, versus how much BI work. There are organizations which need to pull together over 6-8 sources of data, in large volumes (say over 10 Terabytes for 12 months data). I would say this is a DW environment, where a lot of integration is required. On the other hand, many organizations may need to pull BI from only 1-3 sources, or have very small data volumes (under 1 Terabyte). For the first type, having a DW is probably an essential pre-requisite for BI. For the second, it is not so much. The 2nd type of organization may even implement a BI tool directly on top of their operational source systems. My point is that it is easier to off-shore / out-source the DW work, but not so much the BI work. It’s important to keep the BI work on-shore as much as possible. I’d recommend a 70% onshore ratio for BI work. If you are building a fresh DW, it’s probably best to give responsibility to the same party for the BI, so that there is a single vendor to hold accountable. But even if you are going with an off-shore DW + BI implementation, insist that the BI team is predominantly onshore.  But if you are basically doing a “BI only” implementation, it’ll be better to find a local vendor. BI only iterations tend to be smaller (can be about 1 to 3 months). But where a new DW needs to be set up or new sources added to an existing DW, then it would be a longer project.


Off shoring is other dimension in outsourcing, where based on understanding of BI program, it can be thought of what can be delivered from offshore without degrading the quality of deliveries, over all. In any case, your offshore supplier should play the role of a partner in successful delivery of BI program. It is important to recognize that Business Analysis, Requirements Gathering, design documentation and Test Plans are the key to delivering a successful BI or DW Project, and these tasks must be performed on the client site by people that not only understand the Technology to be implemented, but also have Subject Matter Expertise. Off-shoring works, But ideally part of the off-shore team (30%) should travel and remain on-site for the duration of the project. If it is going to be a long project then plan to rotate the on-site visiting team. This increases exposure of the off-shore team to the local business customers, and IT staff. It also ensures someone goes off-shore who has personal relationships and understanding of the customers IT environment.

Considerations during Outsourcing

  • Involve your outsourcing supplier at the beginning of program and start involving them very closely with your BI program, that would set the stage where at later part of program you can think of portion of program or bundled deliveries to be outsourced.
  • For those services where requirements are not clear, or change often, and performance of services are difficult to measure, like a nice complex DWH and BI development project, you may go for outsourcing.
  • Outsourcing can be done with DWH/BI program, but one should not start it without proper due diligence and proper thought process in mind
  • Outsourcing of any application environment is something to be considered very carefully and that is double true for BI/data warehousing as the volatility of the environment is much higher than for any operational OLTP system
  • Information Security can be a road-block. You should be clear on 3 things (a) How sensitive Information Security is for your organization? (b) What concerns does your Information Security officer or organization have about the project? (c) How will your vendor address these concerns, and satisfy Information Security? If you have a dedicated Information Security officer, ask them what their concerns would be. If your source data contains information that needs to be securely managed (credit card numbers, health-care details, addresses) and is regulated, then you may want to setup a remote-desktop capturing solution to help the remote team access local systems, without being able to copy any data. Depending on your budget, you may also invest in a test-data management tool, or a data masking tool, to provide the off-shore team test data that is anonymized, but still useful. Bottom line, it can be managed, with relatively little overhead, but you need to ensure your Information Security team buys-into the controls in place.

 What works for what?

Roughly an estimated BI Project life cycle would include

  1. Project Initiation and Analysis:
  2. Planning and Designing:
  3. Development/Testing:
  4. Go Live
  5. Support

Nevertheless it is time and again proved that outsourcing is successful provided if you take care certain business perspective in order to manage your offshore team. This question whether to could be now has no meaning.

Below is a description which could be a better plan for Outsourcing,

  1. Project Initiation and Analysis: Could be Outsourced but needs longer onsite visits for offshore business heads/experts to understand the environment to Analyze the existing business models of the industry
  2. Planning and Designing: Could be outsourced with short term onsite visits for offshore experts, this area is the technical and functional experts who needs to work together to provide an overall design and upcoming plan for the BI environment.
  3. Development/Testing/Support: This could be completely outsourced. The crucial part here is communication channel. The better the communication, the more service you receive from offshore. To build up the environment as per the agreed terms one need to have proper communication from time to time with offshore team, so that they could deliver the required development. Most of the time this area is misunderstood from the company’s perspective as they always feels that they have provided enough information. No one thinks it is a necessary to understand how much transition is being done within offshore team members, as they are the people who cater further services. However the company provided information at the beginning that does not really give full picture of what company needs. The co-ordination happens only when client gives a better time to their offshore team. There is always a possibility that few things are forgotten once after the analysis and few things are placed in the document after the analysis, and few things are not focused by company business consultants even before finalizing documents, even under 6-sigma there is a possibility for an error. So it significant that IT industry runs with communication, where there is less communication there is always a danger for disaster. So if this is handled with due care you are always successful in off-shored outsourced projects.
  4. Go Live: This once again needs Onsite Visit by offshore team for giving the feel of end deliverable.

Hope I could put the points, as I tried to use very few technical terms in order to present it in simple manner for better understanding about how offshore and outsource models would work.
So I conclude by saying outsourcing provide you follow certain steps as above or you could gauge according to the company needs and understanding. Depending on your organization’s maturity to off-shoring, the type of project activities can be done; it is possible to look at optimized off-shoring. You could also look at a staggered approach where learning of one release are incorporated into the next and progressive increase the level of off-shoring

To know more on ZSL’s BI services and solutions, Contact Shaughn Knight.

SmartPrise BI for Healthcare, Banking, Finance, Telecom, Pharma & Life Sciences, Travel & Logistics, Wholesale & Retail

26 Mar

ZSL’s SmartPrise BI® is the complete end-to-end Enterprise Intelligence solution for small-to-mid enterprises, which enables them to monitor, report and analyze their business performance effectively. The solution enables the enterprises to transform data into business-critical information that helps them to scale as well strategically plan to improve their business performance. SmartPrise BI Mobile for Health is developed based on Cognos, SSRIS, Business Objects, Spotfire, Xcelsius and can fit with any leading ERP & CRM applications that include Microsoft Dynamics, Infor, SAP & Oracle.

SmartPrise BI® suite provides enterprises accurate, consistent and clear data in the form of reports, scorecards and dashboards that acts as a key information for decision and policy makers to give consents, frame policies and guidelines and allocate funds for different planned and ongoing activities across the organization. The suite is addressed to meet the intelligence analytics needs of wide range of industry verticals which includes Healthcare, Banking, Finance, Telecom, Pharma & Life Sciences, Travel & Logistics, Wholesale & Retail.

ZSL’s SmartPrise BI® suite includes:

  • Enterprise Data Warehousing: ZSL follows on industry best practices in developing and delivering data warehousing platforms that span the business and analytical data warehouse needs of the enterprises.
  • Enterprise Data Management: the platform brings together the various data sources through integration between various application systems such as CRM, ERP, Legacy and third-party applications and is organized and managed through well-built service oriented data architecture.
  • Enterprise Data Delivery: ZSL’s SmartPrise BI® suite is flexible and agile that enables the users to have data drilled to any nuances and is delivered in any preferred format such as pie-charts, graphs, dashboards, reports and more. The reports can also be posted into a portal, emailed to users or allow for web-based access.

SmartPrise BI® suite is available for multiple deployment models – On Demand, SaaS & Cloud.

SmartPrise BI® Mobile
The mobile enablement of SmartPrise BI® suite enables the end users to access the mission critical reports over their smart phones and tablets such as iPhones, iPad, Blackberry, Windows Mobile & Brew devices.

Key Benefits

  • Key information that analyses your present and past business performance and guides the decision makers to frame and consent policies and processes suitable to the organization at time of need
  • Serves as a yardstick to measure your employee productivity, operation efficiency and business performance as a result of your new policies and programs
  • Proven and successful methodologies to extract, manage and deliver data
  • Centrally managed data, business hierarchies, rules and calculations to eliminate data silos and inconsistencies throughout the organization
  • Proven and cost-effective BI&DW methodologies built on prudent architecture powered by IBM Cognos which offers seamless integration between various data sources and compatible for SOA, Web 2.0 and BPM capabilities
  • Easy to interpret and analyze data using reports, charts, scorecards and dashboards in preferred formats that has a rich new look & feel and instantly accessible over web and mobile devices
  • Faster implementation services and simple configuration procedures saving 30% of your time and money involved in implementation and roll-out
  • Flexible, role-based security model to protect the reports and reporting resources appropriately and also includes extensible interfaces for integrating other security models if desired

Is your organization looking for a BI tool? Have your organization chosen the right one?

Email me your interests Shaughn Knight, AVP – Business Development and Inside Sales Operations.

Penning the Use of Big Data Analytic in your Organization

23 Feb

Companies have been stacking and analyzing huge volumes of data since the inception of the data warehousing drift in the early 1990s. From terabytes the rate of growth in data volumes has reached to petabytes and continues to escalate as organizations seek to stack and analyze greater levels of transaction details, as well as Web- and machine-generated data, to gain a better understanding of customer behavior and drivers.

Why Big Data?

There has been a lot of talk about “big data” in the past year, what is big data? Why are we are talking about big data today?

Big data is nothing but the term that describes the voluminous amount of unstructured and semi-structured data that are created by an Organization i.e., data that would take too much time and cost too much money to load into a relational database for analysis.

There are several factors influencing to talk about Big Data

Varying data types: Until few years ago it was easy for organizations to capture the data that was transactional in nature and numeric to fit easily into rows and columns of a relational database. But today, the growth in data has predominantly increased from websites and social media contents that has made organizations find it difficult to structure the data

Advanced Hardware Technologies:  The advancement in price performance and technology of the hardware materials has finally made it easy to store and analyze the huge volumes of data at affordable prices. Vendors exploit the technology advancement by developing high speed analytical platforms to accelerate large volumes of data, while the open source community has developed Hadoop, a distributed file management system designed to capture, store and analyze large volumes of Web log data, among other things.

Outsourcing Big Data: Because of the complexity and cost of storing and analyzing Web traffic data, most organizations traditionally outsourced these functions to third-party service bureaus like Zylog. As the size and importance of data analysis increased, many are now eager to outsource this data to gain greater insights about customers. At the same time, virtualization technology is beginning to make it attractive for organizations to consider moving large-scale data processing outside their data center walls to private hosted networks or public clouds.

New and Exciting:. The biggest reason for the popularity of the term big data is that Web and application developers have discovered the value of building new data-intensive applications. To application developers, big data is new and exciting.

Use of Big Data Analytic

Now that we understand the business context for analytical platforms, an analytical platform is a data management system optimized for query processing and analytic that provides superior price-performance and availability compared with general purpose database management systems.

According to a survey, 72% of the organizations had purchased or implemented an analytical database whereas 46% have no plans to do so, 42% are exploring the idea and just 12% are currently evaluating vendors. On the whole, about 75% of the organization will have an analytical platform in the near future.

Implement a new BI architecture

The BI architecture of the future integrates traditional data warehousing technologies to handle detailed transactional data and file-based and non-relational systems to manage unstructured and semi-structured data. The key is to incorporate these systems into an amalgamated architecture that enables casual and power users to query report and analyze any type of data in a comparatively unseamed manner. This integrated information access is the hallmark of the next generation BI architecture. More immediately, companies are using Hadoop to preprocess unstructured data so that it can be loaded and integrated with other corporate data for reporting and analysis. This allows BI and ETL users to use familiar tools to query and analyze data.

Implement analytical platforms that meet business and technical requirements

Today, organizations implement analytical platforms for various reasons. For example, analytical appliances are fast to deploy and easy to maintain and make good replacements for Microsoft SQL Server or Oracle data warehouses that have run out of gas and are ideal as freestanding data marts that offload complex queries from large, maxed-out data warehousing hubs. Analytical databases, as software-only solutions, run on a variety of hardware platforms and are good for organizations that want to tune database performance for specific workloads or run the RDBMS software on a virtualized private cloud. Analytical services are great for development, test and prototyping applications as well as for organizations that don’t have an IT department or want to outsource data center operations or get up and running very quickly. File-based analytical systems and non-relational databases are ideal for processing large volumes of Web traffic and other log-based or machine-generated data. Organizations need to carefully evaluate the type and capabilities of the analytical platform they need before purchasing and deploying a system.

Choosing a Vendor

When an organization is implementing or purchasing an Analytical database from a vendor they need to keep in mind the 4 important criteria before choosing them

  • Whether the selected vendor will meet your requirement?
  • How successful the vendors are in implementing an analytical platform?
  • Whether the vendor is liked and trusted by other organizations?
  • How efficient is their support and services?

Interestingly the pricing, customer references and vendor incumbency should be considered as minimum qualifying criteria.

A vendor should have the ability to meet more of a customer’s requirement. This is because many analytical platforms implemented by the startup vendors are new to the market and heavily priced and customers might not know the exact value of the product. So Organizations should make sure that the product they are planning to implement meets their current and future requirement of the DW architecture. Also, Organization should look for the quality and responsiveness of the vendor to meet their needs.

How can your organization choose the right vendor? How can you get benefited by Big Data Analytic?

Email me your interests Shaughn Knight, AVP – Business Development and Inside Sales Operations.

Impact of BI on Organizations’ growth

6 Feb

BI GrowthIn today’s churning market, every other organization is searching for a BI system that can support and handle their organizational requirement such as decision-making processes, demand generation, predictive analytics etc to survive the global market and to gain competitive advantage. The spread of Internet, adoption of digital marketing strategies and use of web based applications has allayed the organizations with choices of capturing the user data electronically and streamlining the decision making process. This is being the major factor for an exceptional growth of BI adoption globally. Potentially Bi creates a significant measurable value for organizations across various industries. The use of these techniques and technologies delivers a quantitative performance and higher ROI to organizations thus adopting BI. The main intention of this article is to concentrate on the managerial and organizational aspect of Business Intelligence

The adoption of Business Intelligence systems is vital to the smooth and coordinated operation of each and every organization. However; they are becoming more complex day by day. New sets of consumers which were not present before are entering market continuously. So the taste, demand and expectations of the consumers are always evolving. If business organizations fail to understand their markets and consumers then they will probably fail to achieve their organizational business goals as well. The best way to gather these in depth information is by using intelligence services which highly rely on sophisticated technologies.

Key determinants of the success of Business Intelligence systems

There are few factors that determine the success of BI system. Most importantly a company should be unified in contributing their responsibility towards a BI process. It is not the responsibility of a single department of a company; it’s almost the responsibility of all the other departments to contribute for the BI process. Secondly, common definitions are required to be made available before approaching for a BI Solutions and also the current BI stack, Processes and Organization structures are to be assessed. A preplan regarding storing the data, understanding the users are also major factors influencing the success of BI implementation.

An organization also needs to decide very early of the planning phase whether to build or buy data mart for their system. Considering all the business Intelligence components choosing a good system integrator and starting with high value but simple business component are always the foundation of a successful BI system.

Whose responsibility is it to initiate and implement the BI system?

Initially it’s the responsibility of the top management to realize the need of such a system. The second phase requires them to consult about it with the IT consultants within the organizations. The third phase should involve an open discussion between all the department managers of the firm.  A separate board of members needs to be created from there on. But the key factor is to remember that when we talk about BI it means that the entire organization is someway responsible for a successful initiative and final implementation.

Impact of successful adoption of the BI system

More accuracy in decision making, a quick upraise in the profit of your entire business, greater customer satisfaction these are the most visible impact of a successful implementation. But it must be cited that it may take quite a few long before an organization can observe an immense change in numbers in all these areas. This entirely changes from organization to organization.  The managements in all the level of an organization will start to get a broader picture of their business processes that is for sure. As a result accountability will increase from day 1. In some cases a decrease in overall expenditure of a company can also be expected. Business and decision making processes will take less time and the overall pace of the company will increase as a result of the implementation.

How can your organization adopt successful business intelligence implementation? Email your scenarios to Shaughn Knight, AVP – Business Development and Inside Sales Operations.

BI/DW Services for Retail Industry

11 Nov

Retail is one of the most diversified Industries standing at its point of inflexion, waiting for the boom to take place in the vertical industry arena. It is observed that the retail enterprises face numerous challenges and competition due to the fact that the players in the retail markets have not adopted the ability to react quickly and decisively to the market trends and the ability to facilitates their individual clients with tailored products and services; adding to the challenge is the sustained profit that are moderately small. Apart from these challenges, if you are a retailer you also need to focus on few challenges such as choosing the right product to sell, selecting the right supplier for the product and appropriate shipping options, well understanding of the customer expectations and pricing, Anticipating and forecast stock and inventory and so on.

To overcome such challenges you need a framework that should be very effective in means of organizing and analyzing the vast amount of information generated in the retail business, align your business with client needs, differentiate your product than that of your competitors, should optimize product mix and space utilization, and finally should help you to generate a more effective business mode to keep you always ahead of the profit margin. This can be done only if you have a Business Intelligence (BI) system in place. Retail is all about getting the right product at the right time at the right price. However, the right location and mix of web and brick and mortar facilities also plays an important factor in the industry. If the customer is unable to find your business obviously they are not going to reach you.

You may think, gathering and analysis of business intelligence is an easy task. Trust me; it is not. The retail industry by itself is awash in best of breed, enterprise and legacy systems to manage everything from

  • Traditional retail information, including point of sale data, gross margins, turns, and gross margin return on inventory investment (GMROI);
  • Market data, including market share and competitor pricing;
  • Promotional data, including special pricing offers and vendor contributions, such as promotional allowances and coop advertising fees; and
  • Client data, including demographics and various loyalty and client value metrics

If the retailer is to remain competitive, executives, managers and business users must have access to the most complete information with full insight into results and critical issues and the ability to quickly analyze, present and report these results to support decisions and adapt to the changing market.

Advantages of using a BI framework:

  • Provide you simple dashboards that enable swift reporting and analysis of information integrated from numerous sources. These tools digest large volumes of information and convey it in an intuitive format, making it easy to classify and respond to critical, time-sensitive events. They also help in exploring issues and trends without getting completely lost in a big pool of information.
  • Deliver information through personalized BI dashboards and charts, graphs, gauges, automated alerts and other views designed to meet the needs of the individual user and to support their role and function
  • Contour and optimize resource capacity and merchandise management
  • Determine and manage supplier performance to ensure appropriate inventory and stock management
  • Provides you the ability to analyze and adapt new and advanced marketing and ecommerce strategies and customer buying capabilities
  • Perform market share analysis and market research to support marketing, sales and targets
  • Enhance your category management
  • Compile and analyze brand and marketing research
  • Perform Integration and analyze information from key performance metrics such as financial data, inventory, etc., and CRM systems with unlined integration of various formats and stunning reports and graphics providing accessibility across the enterprise in every location with integration and information sharing, collaboration and consistency irrespective of the location of the users
  • Design effective marketing campaigns for specific products by identifying opportunities
  • Gather and analyze data to determine appropriate stock and inventory levels to meet demand and avoid overstock or shortages
  • Enhance you financial performance and enables the user to monitor the financial health of the organization and create and share reports to comply with government and industry regulations

For more information on Business Intelligence for retail industry or any other industry queries please click here

BI/DW Services for Manufacturing

2 Nov

With the enhancing competition and ever more demanding customers, manufacturing is never easy. The uninterrupted production and machines scheduled across multiple plants or production lines to meet orders or forecasted demand makes the scenario even more baffling. The outcome of this scenario creates a deep impact on the complete industry and success counts on accurate materials planning.

Managers and analysts in the manufacturing industry who are involved in reviewing metrics such as production capability, planning production schedule based on their current inventories should ensure that the availability of the raw material for their production unit is abundant and make right decisions on plant reallocation for manufacturing their product when required. . This amount of planning requires a basic analysis and an advanced analysis that will help to optimize their production. A basic analysis includes real time status of plant utilization and an analysis of the advanced market demand trends versus the amount of production done by the unit. While an advanced analysis includes analysis of commodities used in the production, a detailed forecast on the output of the production machine and additive programming to optimize production resources.

Following business area are prime areas of concern for manufacturers:

  • Manufacturers need to have a bird’s eye-view of their customer information that will help the sales team to coordinate and collaborate their customer interactions.
  • Improve customer satisfaction.
  • Lead time to fulfill customer orders across sales and distribution channels.
  • Improve “order promising” (i.e., when a customer is promised delivery or issue resolution) through analysis of historical statistics, expected lead time, and inventory levels
  • Analysis of usage of products to go for new range of products.
  • Predict and prepare inventory and production levels.
  • Benchmark distributors, and geographies against each other in an attempt to foster increased attention to goals and metrics, as well as reward high performers and aid underachievers.

To overcome they need to maintain optimum level of inventory so as to avoid overstock / short-supply and bring innovative and profitable schemes at marketing level. Business Intelligence is the right tool that will helps in achieving this.

BI can also be used to increase the flexibility and speed of operational reporting.

  • Quickly generate established reports
  • Easily create ad-hoc reports
  • Isolate specific problems
  • Analyze data across multiple systems
  • Integrate new data sources

BI helps manufacturers a better visibility of their financial performance and the insight and understanding to improve it i.e., it provides the solutions for cost and profitability analytics and solutions for operational planning and budgeting. Being able to quickly assess the impact of internal and external changes, BI helps such companies become more agile and better able to keep the bottom line on track.

BI helps managers to be equipped with state-of-the art and exact information to take critical business decisions rather than going on assumptions of a situation.

BI helps to improve communication across increasingly complex manufacturing supply chains, while satisfying customer demands for new products and product enhancements.

How BI helps companies in the Manufacturing Sector:

  • Increase the value of customer relationships
  • Respond quickly to changing markets and company sensitivities
  • Accelerate new product time-to-market
  • Reduce inventory investment
  • Improve planning, scheduling, and the procurement schedule
  • Maintain and develop quality assurance
  • Select and apply world-class technologies

For more information and to find how your company  can get benefited by BI, Please click here