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February 28th, 2014

BI_Feb24_BIf there is one thing all businesses rely on it's data. As the integration of new systems and features continues, the amount of data available to a businesses grows. In order to be able to get more out of this data, businesses have started looking at adopting Business Intelligence (BI) systems. These come with their own language, and three of the more confusing terms are data mart, data warehouse, and data mining.

What is a data warehouse?

The concept of a data warehouse is an interesting one and also a difficult one to define and pin down largely because it can cover such a broad area. The most concise definition we can give is that it is a database that integrates data from many different locations and databases into one consolidated database.

Data warehouses store both current and historical data, and rarely contain unique data. Instead, they aggregate data from other sources in order to make this more accessible. They might store important information from sales, marketing, ERP, customer interactions, and any form of database in order to quickly generate BI related reports.

The name undoubtedly conjures up the idea of a large warehouse-like building storing infinite amounts of data. However, most data warehouses are actually tables which are created by taking data from various sources and cleaning it up so that relevant data is stored in the warehouse in a way that makes it easier to reach when needed.

What is a data mart?

A data mart is a smaller data warehouse that stores data. These are based on a specific area or business function e.g., finance or marketing, etc. In fact, most modern data warehouses are actually made up of a series of smaller data marts.

The key difference between a data mart and a data warehouse is that data marts are usually smaller, focusing on one specific area, while a data warehouse covers the whole organization.

What is data mining?

When talking about Business Intelligence, many experts will refer to data mining. This is the act of analyzing data in order to identify patterns. The data that is mined can then be transformed into useable information. Many companies store this mined data in databases, a data warehouse, or a data mart.

Want to learn more about these terms and how your company can benefit from a BI solution? Contact us today.

Published with permission from TechAdvisory.org. Source.

January 30th, 2014

BI_Jan27_BData has always been one of the most essential components of any business. Without data, many businesses would be unable to make essential decisions or even track their success. For companies that track this, they have likely heard of business analytics. While this term is popular, it can be confusing to actually nail down what this is.

In this article we will take a brief look at business analytics and why it is so important to businesses of all sizes.

Business analytics defined

When experts talk about analytics most audiences will agree that it is the analysis of data and statistics. The vast majority of business owners have some experience with analytics, with some having even taken courses on it at University. This being said, the idea of business analytics is often hard to pin down - ask 10 people and you will likely get 10 different answers defining what exactly it is.

We like to define business analytics as a process rather than a science. This process uses skills, business experience, technology, applications, and common business practices, to enable business owners, managers, and employees to explore past performance. Simply put, it's the study of the past performance of a business.

With most businesses, the goal of business analytics is to gain insights into the state of the company, and even drive future decisions based on existing data. If you can successfully implement a business analytics process, you and your employees will gain a higher understanding of your business which will lead to better decision making abilities and even higher growth and profits.

What makes up business analytics

As we noted above, this is a process that involves a number of separate components. Four to be exact:
  • Analytics - Using modern data mining and predictive tools to identify patterns that can help make better business decisions and give managers foresight into potential future trends. Usually the questions answered include, "What is the best outcome?", "Why did this work?", etc.
  • Data management - This covers the collection and storage of data. Concepts include how and where the data is stored, who has access to it, how it is accessed, and even when it can be accessed. Some examples of this include using cloud-based storage or even a storage server that is hosted in the office. When looking at data management in terms of analytics, most managers will concentrate on what has worked in the past, why it worked, and what will work in the future.
  • Business Intelligence - This is the use of reporting tools and dashboards to gain an understanding of largely event-based questions like, "How many?", etc. When you implement business intelligence operations you will normally gain better insights into current events and what happened in the past to influence them.
  • Performance Management - This broad term covers actions and tools that are used to track and manage business performance. This includes tasks such a financial reporting and budget forecasting.
The main reason businesses implement the components of business analytics is so that they have a way to not only harness the data their business generates, but to also leverage it in a constructive way so that their business can make better decisions. If used properly, it really helps businesses answer two of the hardest questions to answer: "What do I need to know?" and "What do I need to do?"

If you are looking to learn more about using business analytics or the components that make up this process, contact us today to see how our solutions can help.

Published with permission from TechAdvisory.org. Source.

January 3rd, 2014

BI_Jan02_BBusiness Intelligence – the collection and transformation of data into useful information that can be used to make better decisions – is one of the more important business processes, and saw continued popularity in 2013. Because of this increased use, there are a number of trends that we believe will be become favorable in 2014.

Here is an overview of the potential Business Intelligence (BI) trends we could see emerging and growing in 2014.

1. BI is more accessible

Historically, to get the most out of Business Intelligence you need to be experienced or to employ a data scientist. Over the past couple of years BI methodologies have become easier to execute. Throughout 2014 it is highly likely that we will see most ordinary business users continue to gain skills in this area and consequently carrying out business analysis and BI activities.

This means we should see an increase in the number of programs that are user-friendly, while still providing the powerful tools that experts have been using.

2. BI and Big Data solutions forecast clouds

Cloud-based solutions have helped allow small to medium businesses to access tools that were previously only used by enterprises. Many BI solutions are starting to incorporate cloud-based versions and this trend will undoubtedly continue in 2014.

These solutions will put important data in the hands of individual businesses, while also providing them with the ability to store and analyze their data with ease, as long as they have an Internet connection. Many of these solutions also allow for increased collaboration and some even have mobile apps which could help make adoption easier.

3. Predictive analytics are more accessible

Predictive analytics is the process of looking at existing data for trends and important information that you can use to help make predictions and decisions. This type of analysis has largely been the domain of experts and large companies, but in 2014 this process should become increasingly available to small businesses.

4. Social data is even more important

The majority of customers are active on social media. This has led to a huge source of potential information that businesses can benefit from. From Likes to Shares, Comments, etc., companies will begin to pay closer attention to this data. It can help businesses gain insight into brand awareness, how relevant they are to customers, and even gain important information they can use to conduct competitive analysis.

5. Storytelling from existing data

One of the main objectives of analyzing your data is so that you can tell a story with it. If you have no narrative arc attached to your data, it is highly likely that the message you want to get across won’t sink in.

By visualizing your data in a way so that it tells a story you will be better able to gain a concise meaning from an overwhelming amount of data

If you are looking to learn more about BI and how it can help your business, please contact us today.

Published with permission from TechAdvisory.org. Source.

December 5th, 2013

Bi_Dec02_BIt's not uncommon for established small to medium businesses to hit a bit of a wall when it comes to sales and growth. Often, after a period of great growth, businesses can begin to see sales and profits level off. This stabilization can be tough to break out of, especially if you want to continue growing. One way businesses can break the cycle though is by analyzing existing data to identify patterns.

In order to move your business forward and grow, you should analyze and try to interpret the data in your organization. This includes everything from previous financial statements, year-on-year sales figures and numbers, and even KPIs or estimated Vs actual figures. By looking into this data, you will eventually begin to find patterns which can be useful in not only helping you figure out the current state of your company, but in identifying where it is going.

Why should you analyze data for patterns?

Most experts agree that there are four reasons businesses should be analyzing their data:
  • You can better evaluate past performance.
  • You can assess current status.
  • You can more accurately predict future potential.
  • You can make better decisions that will maximize profits and resources.
Essentially, when you track and analyze your data you should be able to spot potentially important patterns that can allow you to make better decisions, quicker, and usually with more accuracy. It is the analysis of patterns that also makes up an important part of Business Intelligence.

What types of patterns should you look for?

Many small to medium businesses generate a wide variety of data, and it can be a challenge to narrow down what data types and patterns to look for. To start with, many businesses focus on three main patterns:
  1. Industry comparisons - By looking at the financial information from other companies in your industry, you can detect overall industry performance and identify any anomalies. For example, if some companies have increased sales and profits, while others are static or decreasing, the more successful businesses may be doing something that you can also adopt in order to improve your sales.
  2. Actual vs planned performance - By looking at your actual and planned sales you can see how the company is doing e.g., were sales lower than expected? If yes, you can begin to look into why. When compared year-over-year you should be able to see patterns emerging that help you resolve issues or take advantage of new opportunities.
  3. Trend analysis - This is comparing current and past performance with the aim of finding out where or how your business has changed. Some examples of patterns are how sales are trending, how profits are doing, and cash flow. From here, you can determine how differences have occurred and what corrections are needed.

How do you analyze data and identify patterns?

Many businesses rely on spreadsheet software, such as Excel, to store, manipulate, and visualize data, to ultimately spot patterns. But this requires a fair amount of effort to establish and maintain, and as the spreadsheets grow, operations can slow down.

One option many businesses explore is utilizing Business Intelligence software, which allows businesses to easily track data and identify patterns, among other uses. There are a wide variety of programs, so if you are looking to begin tracking data and analyzing patterns, try contacting us today to see what solutions we have for you.

Published with permission from TechAdvisory.org. Source.

November 5th, 2013

BI_Nov05_BToday’s savvy business owner gathers information in a way that consistently reveals insights into corporate operations. Through careful and deliberate examination of all aspects of your business, a portrait can emerge that points the way forward toward a profitable tomorrow. The key is to know which data is not relevant and which is by employing the right tools during the information gathering process.

Many small businesses depend on their IT personnel to provide data that will enhance their business. However, there’s a difference between mere data and enriched information that improves performance. For instance, you might be surprised to find that page views are largely useless. This figure tells very little about how people are actually using your site, which is the most important information you can have. Data that leads to improvements is more than just information. It’s intelligence. There are many types of information which can help businesses become more intelligent.

Visitor flow Visitor flow follows how users navigate your website. The most important point is to learn about where your customers enter your site, and where they leave. Simple numbers of visitors is not as useful. Let’s say that you are running an online store and that 350 visitors left your site on the 'confirm order' page. This might suggest there’s some type of sticking point related to this page. It might be that the wrong orders are loading. It might be that a sudden tax add-on that wasn’t fully clarified caused users to cancel the purchase. Regardless of the reason, this type of business intelligence may help you make positive changes in the online experience you create.

Traffic sources Traffic sources tell you where your customers are coming from and therefore what’s driving people to your site. Wouldn’t it be helpful to know the type of sites which are leading to yours? With that information, you might step up advertising and marketing within those sites, and bring even more business your way. Traffic sources are also a great way to measure the effectiveness of advertising.

Keywords When you know what keywords people use to find your business online, you can begin tailoring your pages to contain more of them. You can also begin applying those keywords in advertisements, banners, and promotional efforts you invest in online. By better meeting user desire and expectation you can raise your profile above that of competitors.

Conversion rates Your business makes money when people buy your product or services. Conversion rates can help track users through the entire sales experience. By finding out key data about where users spend time online, where they enter the sales experience, and when they leave, you are better able to adjust your product or service, your presentation, and perhaps your website design. By finding peak points of purchase, you can pinpoint successful pages or links too. By finding weak points of purchase, such as abandoned online shopping carts, you might be alerted to tech problems or layout aspects that interfere with more robust conversion rates.

Bounce rates Bounce rates reflect the number of users who visit your site but leave without looking at any other pages. In a best case scenario, it means they find what they are looking for on your site fast. In the worst case scenario, it means that your users lose interest immediately, and big changes on your site have to be made. A high bounce rate can be changed through rich content development that engages users to remain within your site, exploring what your business has to offer in terms of products and services, and more.

Bounce rates are a great example of the difference between metrics and information. IT might present stats that show 3,000 people are visiting a site each day. This might seem like good news, until it's revealed that the bounce rate is 2,999. This is the difference between information and intelligence.

Business intelligence creates a better opportunity to maximize your production and profits. We can help in that process, so get in touch today.

Published with permission from TechAdvisory.org. Source.

October 11th, 2013

BI_Oct08_BDecision making can be among the toughest tasks to do when running a business. Make the wrong ones and you could see profits dip or customers disappear. In order to make better decisions, many companies are implementing Business Intelligence (BI). Because BI can utilize a lot of data, a common way to present is is by visualizing it.

Here are four tips on how to make successful data visualizations - e.g., charts, graphs, flowcharts, etc.

1. They need to be easy to understand When visualizing data, it can be very easy to make the outcome incredibly confusing. By having too many sets of data, trying to compare and visualize too much, or by simply laying information out in a confusing way, you could actually decrease the effectiveness of the message you are trying to convey or lose it altogether.

When creating visualizations, try to get someone who is part of your target audience to look over it and make sure they can understand what the visualization is representing and that it is easy to comprehend. If they can't, you need to go back to the drawing board and try to come up with a way to present the data where the intended audience can understand and follow it easily.

2. They need to cater to the audience The main reason most managers or owners visualize data is to present it to an audience. 99% of the time, this audience is a decision maker and you are trying to get them to decide on whatever the data visualization is representing.

Therefore, when setting out to visualize your data you should first define an end goal - what you want the audience to do with the data. In order to do this, and to develop a successful visualization, try considering these three questions:

  1. Who exactly is the audience? - Because the audience will ultimately be making the decisions, you should define who they are. Focus on how much they know and how comfortable they are with the subject, and their position within their organization or outside it. From there you can begin to tailor which data to present and how.
  2. What does your audience expect from the data? - This can be achieved fairly simply by actually asking key members of your audience. Try reaching out in an email and asking about their expectations. If they say they want something simple to understand, don't use overly complex graphs or visualizations. Focus on what type of information is most important to them. For example, if you are visualizing sales data for a finance team, marketing related data may not be overly relevant.
  3. What is the role of the visualization? - Visualizations have many roles. Some are intended to educate, while others are aimed at prompting the audience to act or ask questions. As a general rule of thumb, educational visualizations should not create questions, while actionable ones should.
3. They need to have a clear framework or layout When visualizing data you need to ensure that you develop a layout or framework that is clear and easy to follow. This means focusing on two main areas:
  • Semantics - The meaning of the words and graphs used. Remember that simple words like 'or', 'and', etc. can drastically change the meaning of a sentence and possibly make it unclear. Because of the visual nature of this method you will need to be crystal clear with accompanying words and titles. The same goes for the visual side. If you are using icons or images, they need to look like the data they are representing and be clearly identifiable as different from other sets of data.
  • Syntax - This is more how the words and visuals are used and represented. If visual and accompanying words are not laid out in a clear and logical manner, there is a high chance that the message or action you want to convey will fail to be grasped. Also, pay attention to how you present the data. If you are using a graph with lines, most people will view this as trend related, even if you intended to compare the results to different sets.

Above all - They need to tell a story The most successful visualizations tell a story about the data. Unlike TV or movies, you aren't telling a story for pure entertainment. The story should be related to how the audience will be affected or can be helped by the data represented in the visuals. If you are struggling to find a way to tell a story, try actually explaining the data. By knowing it inside and out, you will likely be better able to come up with an explanation that you may be able to weave into a fluid story for your audience.

If you are looking into visualizing your data, or improving how you present it, why not contact us to see how our systems can help.

Published with permission from TechAdvisory.org. Source.

September 13th, 2013

BI_Sep09_BBusiness Intelligence has become a popular concept among many small business managers and owners - who doesn't want to be able to harness data to help make decisions? One of the more popular ways businesses manipulate data is by visualizing it. While this can be useful, it's not perfect for every occasion. So, the question is: when should data visualization be used?

In order to know when data visualization should be used, it's a good idea to start with why we even use it at all, and what makes it work.

Why visualize data The whole point of taking data and turning it into more understandable information is so that we can utilize it to make a decision or take action from what we learn. Data visualization is just another way of turning data that we can't read or understand and turning it into something that we can see and use. In other words, creating information with visible insights.

In general there are three reasons why you might want to visualize data:

  1. Education - Many visualizations are valuable because they educate or report on a specific topic. These can also provide insight into changes related to a topic over time, so that you are able to understand trends and learn from them.
  2. Exploration - As more data sets become increasingly larger, it can be tough to easily spot relationships between them and create predictions. Visualization can make this easier to understand and manage.
  3. Confirmation - If there are assumptions about a subject, and data has been collected, visualizing it can be a useful way to prove or disprove the assumption.
What makes a good data visualization There are three main aspects of information that make up good effective data visualizations:
  1. It's interpretable - With the sheer amount of data available to managers and owners you can be sure that some of it will be useless. It could be the data collected doesn't have enough relevant information, such as where it comes from, when it was collected and by whom. If you can't interpret data, you likely won't be able to gain insight from it which makes it hard to actually visualize what information it is you have.
  2. It's relevant - The data shown needs to provide valuable insight to the audience and therefore needs to be relevant. Beyond that, it also needs to align with the overall purpose of why it's being examined.
  3. It provides something new - Above all, the visualized data should show some new findings or provide insight that you did not know before.
If the visualization fails to meet any one of these three aspects, you will end up with an outcome that doesn't provide value and will likely be ignored or viewed with skepticism. In this case it is probably not worthwhile trying to visualize it.

If you would like to know more about how you can visualize data, or how you can harness the data in your organization, contact us today to see how we can help.

Published with permission from TechAdvisory.org. Source.

March 28th, 2013

BI_March27_BData: A set of values that belong to a set of items, is important to every business; it is largely useless in it's raw form though. Through the use, manipulation and analysis of data we get useful information that we can use to make decisions, gauge the health of our company or even tell how popular our Facebook Page is. While it is important, data can be hard to analyze without the right tools.

Here's a brief overview of five data analysis tools that you could use in your business.

BigML

One of the more common uses of data is to help a business manager make predictions. We all know predictions are among the hardest things to do. Enterprises hire staff and invest in systems solely with the aim of making predictions. If you're a small business, you likely don't need expensive software that is hard to use.

Enter BigML. How it works is you define and upload a set of data and format it. BigML will then take that data, help you to create a prediction model which you then can apply 'what-if' variables to and have it generate predictions. The site runs on credits; you pay for a set amount of credits and each part of the process - dataset, model and prediction - is worth a certain amount of credits. Prices start at around USD$6.50 for credits, which gives you 10MB of data, 5MB worth of models and 10K predictions based on this data.

Wolfram|Alpha's Facebook Reports

WolframAlpha is a search engine that collects data and uses algorithms to interpret it. One feature of this site is that you can develop reports, one of the more useful being Facebook Reports. You can access the report feature by clicking here. Alternatively, you can go to the WolframAlpha website and search for Facebook.

This report provides users with a glimpse into their Facebook Page's information. It provides you with information on who are the most active posters, how many shares/likes, etc. you get and other useful information in easy to read charts and graphs. The key here is that the report can show you how customers access your Page and where they come from. You could use this information to see what posts users liked and didn't like, and provide more engaging content.

The basic version of the report is free. More advanced controls and data analysis is available for USD$4.99 a month.

Many Eyes

Many Eyes is a data analysis and visualization tool developed by IBM Research. If you already have data sets then you can upload them to the website and use one of the many different visualization tools to create charts, graphs, etc.

A cool feature of this site is that it has the ability to analyze written documents. Say for example you are writing new content for your website, you can copy and paste the content and get a visual representation of the words you use, how you connect words, etc. If you have a set of keywords you would like to use for SEO and search purposes, you can manually compare them with the visualization. If you notice that an important keyword is missing, or not represented enough, you can go through and re-write the copy a bit.

Best of all, it's free.

Tableau Public

If you have an idea about Business Intelligence, or have worked with data on a regular basis and have sets that are structured, Tableau Public is probably the most powerful free analysis tool available for small businesses.

While powerful, it isn't the most user-friendly of options. To get the most out of this program you are going to need to know the basics behind data analysis. If you feel comfortable with the basics, you'll be creating dashboards, charts, interactive graphs, maps, etc. that look great and can be embedded on your blog or website. Oh yes, did we mention it's free?

Excel

Big data is all the rage these days, it's hard not to hear techies and data specialists talk about it. While it is an important part of many large businesses' data analysis practices, the truth is many small businesses don't need big data just yet. If you have simple data you need to analyze e.g., how many hours have your five employees worked this month? Why not stick with simple spreadsheets like Excel or Google Spreadsheet.

As long as you have data entered in a logical way, you can easily create graphs and charts that can help you visualize and analyze your data.

If you would like help establishing a system that can help you track and analyze your data, please contact us today, we may have a solution that works for you.
Published with permission from TechAdvisory.org. Source.

March 5th, 2013

BI_Feb27_BData is a word you hear continuously thrown around these days. We know that the amount of data generated and available to us is increasing. Most businesses use the data they have as a judge of how they are performing or meeting goals. With the growth of data, analysis becomes increasingly challenging, and consequently many companies have turned to dashboards to help.

A dashboard is an easy to read and comprehend representation of data that indicates the current status of a company. Most dashboards look at a company's Key Performance Indicators (KPI), and display information graphically, and more often than not in real-time. This study of performance is often referred to as analytics, and companies can use KPIs, and the dashboards that represent them, to predict, describe and even change performance.

Dashboards have become an integral part of any analytics process, and can really help a business. However, they need to be implemented properly if a business is to benefit. Here's five tips that can help you launch useful dashboards.

1. Focus on the important Dashboards allow you to track almost any form of data. This doesn't mean you should, however. In fact, it's a good idea to step back and identify the most important, or most integral processes of your business. You could start with two or three of these that you can clearly track from beginning to end.

2. Do your tech due diligence The number of programs and full solutions that offer small businesses dashboards are plentiful. You should think about what exactly you want to track and your overall goals before you talk to a vendor.

With the information and metrics identified, you should look for a solution that allows you to track these to the level you want. If you're only being offered once a week views, for example, and you need updates once a day, you're better off continuing your search.

Beyond this, you should be careful to look at the options each dashboard has, and the information it follows. You don't want to be tracking information you don't need, as this could throw off the effectiveness of the solution.

3. One solution won't fit all It's important to bear in mind that different departments or roles will want to track different information. You should include the different team wants, along with their representatives, when looking at solutions, so you can get a better picture as to what you need.

4. Benchmarks Once you have set your goals or objectives and before you implement your new dashboard, it is a good idea to track any related information. This should give you a solid idea from which you can compare changes once the dashboard is implemented.

This pre-system tracking doesn't have to be long, maybe three to six months - enough time to give you a solid grasp of what you want to look at. After implementation, track the same data for six months and look again. Any changes will become the new benchmark which will allow you to launch new solutions, or gauge effectiveness of the data you are collecting.

5. Back up your data As with any tech system, all dashboard software will have the occasional bug or glitch. It simply cannot be avoided. Developers and vendors know this and many have backup solutions to ensure data loss is minimized. It is a good idea to consult with them to ensure their backup meets your needs, or look for one who can work with existing technology to ensure data won't be lost.

Tracking data and information that is critical to a business's operations can help you gain not only a clear picture of just how well your company is doing, but also highlight any need for changes or improvements. If you would like to find the right dashboards for your business, please contact us, we may have a solution that will drive your success.

Published with permission from TechAdvisory.org. Source.

February 1st, 2013

Data is commonly defined as a collection of numbers, words, charts, etc. Every technological gadget produces data these days, and the processing of this turns it into information. It's this information that we use to make decisions, which generate more data. There is so much data available that it can be challenging to keep track of it all and turn it into valuable information for decision making. Because of this, the idea of big data has arisen. Media outlets have highlighted big data, causing many businesses to become curious about it. Are you one of them?

A study published in mid 2012 by Harris Interactive looked at what exactly big data is. The research polled 154 companies, more than half of which were small businesses, on what they think the definition of big data is. The results? No one really agrees on a definition of big data.

The survey found that 24% of respondents believed it's the technology that allows the management of massive amounts of data, while 28% believed it's the idea of massive growth of transactional data. The survey concluded that nearly 80% of businesses identify big data as some form of opportunity in the near future.

Beware of big data hype This goes to show that businesses are aware of the trend, and may feel that they have to be a part of it to gain any sort of competitive advantage in the near future. However, this is the wrong way to look at big data. The fact of the matter is, while big data is here to stay, many small business simply don't have the resources - monetary, staffing, knowledge, or otherwise - to launch big data initiatives.

Don't not focus on data The amount of data available and being generated is growing at an exponential rate, and even small businesses are overwhelmed with often unintelligible data. The danger is that if you turn your back on data you might soon find yourself lagging well behind your competitors.

If big data and ignoring data are out, what's left? The middle road, or in this case, small data. Take a look at your business and identify and prioritize the most important data for your business. For example, a dentist is probably going to want to know how many patients are walk-ins or appointments. From here, you can analyze the data and begin to pick out trends, anomalies and weaknesses, etc. Taking the dentist example above, if data identifies that walk-ins are 10 times heavier on a Monday morning, it may be better business practice to have more staff on Monday mornings to better deal with customer flow.

Baby steps leads to big data The key is to start in a small and manageable way. Focus on understanding critical data by getting to know how to collect and analyze it. This will provide a platform from which you can launch bigger data initiatives in the future. Once you are comfortable, you can introduce more advanced dashboards to better utilize your data. If you do methodically, you should be aligned perfectly to take advantage of big data when it becomes viable for all businesses.

Interested in learning more about data in your organization? Contact us today to see how we can help you.

Published with permission from TechAdvisory.org. Source.