How SharePoint Can Help Your Business

SharePoint is not just a program or individual solution; it’s a massive platform that provides secure places to store, organize, share, and access information from almost any device.  Able to be deployed within a server environment or used in the cloud, SharePoint is highly scalable, extensible, flexible and cost effective. As versatile as it is ubiquitous, SharePoint can be used to access or create solutions that provide:

  • Websites – for your employees and your customers
  • File sharing and document collaboration
  • Enterprise social networking
  • Organization of people, processes, and projects
  • Custom web parts and applications
  • Enterprise search
  • Standardization and refinement of forms, approval, and workflow
  • Records management and legal compliance
  • Business intelligence and data visualization

The fundamental building blocks of SharePoint are internally or externally facing websites to which users make changes and contribute content. The degree that users can alter or access these SharePoint sites can be limited to ensure information is only available to those who need it or should have it. Changes to information and sites are monitored and controlled.  Groups can set up centralized spaces for document sharing where documents can be stored, edited, and collaborated on. SharePoint’s integration with Microsoft Office online allows users to edit documents directly in their web browser.  Additionally, SharePoint collaboration environments can be extended through the use of apps and web parts to provide additional functions like email alerts, shared calendars, data summaries, and sophisticated tools to search through, securely access, and reuse large amounts of content.

SharePoint can be used to enhance an organization’s ability to manage content and information at the enterprise level. Solutions are employed to manage enterprise metadata, define a company’s best practice for creating documents collaboratively (including versioning and check in/ check out functionality), and enforce policies that govern workflow across a project’s life cycle. In addition, SharePoint can be used to ensure records management regulatory compliance and mitigate legal risk across all of an organization’s content.

SharePoint 2013 has advanced integration with Microsoft’s self-service BI platform. This integration gives users access to PowerView in SharePoint providing numerous ways to visualize data, create easy-to-use dashboards, and share reports with colleagues. Also new to SharePoint 2013 is a focus on social sharing. Microsoft’s acquisition of Yammer allows SharePoint users to engage in threaded discussions, “like” and share posts they find compelling, and connect other users to content.  With Yammer, it’s even possible for SharePoint 2013 to learn from user activity and offer users relevant content automatically. Additionally, SharePoint 2013 users can create and access blogs, wikis, RSS feeds, and other functions associated with top social media platforms.

Big Data – What are the Tradeoffs?

You cannot open a business or IT trade magazine these days without seeing a major article about the impact of “Big Data” on the Enterprise. There is often a lack of discussion of what constitutes Big Data with the unstated assumption that any mass of Enterprise data constitutes Big Data. The “Three V’s” of Big Data are often cited as its defining characteristics: Volume, Velocity, and Variety. But Big Data systems should also be examined and compared to RDBMSs and other systems in relation to another three letter acronym, the CAP theorem, proposed in 2000 by Eric Brewer. The “CAP” of Brewer’s theorem stands for Consistency, Availability, and Partition Tolerance. Brewer proposed that networked systems can have two of these three attributes, but trade-offs prevent a system from having all three characteristics.

Consistency in the CAP Theorem is essentially equivalent to what is known for traditional RDBMSs as the consistent trait of “ACID Compliance” (Atomic, Consistent, Isolated and Durable). This means that a given transaction or interaction will ‘look the same’ across all environments when it is finished (all Inserts, updates or deletions to all affected tables will be the same). Availability refers to the capability of the system to respond to interactions or messages. For example, if you hit “Submit” on a form, does the system respond in some way, or are you left wondering what happened? Partition Tolerance means the system can sustain a failure of a node (whether a particular server or a whole data center) and still be operational. “Fail-over” procedures and mechanisms allow systems to be Partition Tolerant.

Because Big Data systems are distributed across tens, hundreds, or even thousands of servers as well as globally across data centers on different continents (i.e. Akamai content delivery), they excel in providing Availability and Partition Tolerance. However, they rarely target transactional Consistency as their primary benchmark. Most Big Data systems instead strive for “Eventual Consistency”, meaning that within a given timeframe (i.e., a handful of seconds up to many minutes), data will be consistent across all environments. This characteristic is perfectly acceptable for most web content systems, but would not be acceptable for systems such as banking and trading, or real-time monitoring systems in operational settings such as manufacturing or medical systems. In other words, it might not be of utmost importance that you are viewing your sister’s latest comments on the picture you uploaded to Facebook from your phone, or that you are seeing the latest trending Pop culture ‘tweets’ with imbedded links to a YouTube video. But it is very important to both you and your bank that the available balance in your checking account is more than the amount of your current purchase with your debit card ATM, whether you are at the local grocery store or if you are at Harrod’s Department Store in London, England.

Traditional RDBMSs are subject to these same CAP restrictions, but RDBMS vendors have had decades to provide tools and methods to minimize the impact of the choices system architects have to make in dealing with these trade-offs. For instance, transaction logs and rollback methods, mirroring, and fail-over capabilities allow database administrators to recover from system failures both locally and globally to a given point in time. Large companies that deal with global transactions have sophisticated procedures to provide real-time communications and transactions and to mirror whole systems across continents while still providing disaster recovery.

For this reason, most massive web-based systems today are a combination of Big Data systems and RDBMSs. For instance, when you purchase a book online, when you log in and browse titles and reviews, you are interacting with Big Data. But when you enter your credit card information and submit your order, you are interacting with a traditional RDMBS. The ability of the vendor to analyze other customers’ purchases to suggest ‘Other Titles You Might Enjoy’ is based on their analysis of Big Data browsing and purchasing patterns and the web traffic of millions of customers who share your characteristics. To do this kind of analysis in a traditional RDBMS would be extremely time consuming and computationally expensive. To do it in a Big Data system is much faster and easier.

Many vendors and open source projects are seeking to both ease system manageability and narrow the gap between the security and assurance provided by traditional RDBMSs and Big Data systems. Newer Big Data based data management systems, often called “NoSQL” systems (for NotOnlySQL) such as H-Base, Cassandra and MongoDB are attempting to solve many of these CAP theorem trade-off issues. Vendors in this space include 10gen, Couchbase and DataStax. Vendors such asCloudera, Hortonworks, and MapR offer tools that integrate the most commonly used Hadoop-based stacks of Big Data management and analysis systems. The large vendors of traditional RDBMSs such as Oracle, IBM, SAP, and Microsoft all offer either their own versions of NoSQL databases and Big Data management tools, or extensions to their existing products, to try to address the need to integrate both traditional RDBMSs and Big Data systems. These products are evolving rapidly with new releases offering more and more functionality and integration.

This is an exciting time for Systems Integrators and Data Management Professionals as Big Data systems, both in-house and “in the Cloud”, provide previously unavailable flexibility and scalability. But IT management must keep in mind the inherent trade-offs that distributed systems face, whether they are new Big Data systems, or traditional RDBMSs.

Plaster Groups Data & Analytics Consultants can help you manage your Big Data solutions.

Build vs. Buy Software Solution Assesment


Our client, a large local nonprofit, was struggling to manage its priorities and goals. Teams that needed to coordinate their work were using disparate tools to capture and report data, often using different terms with the same meaning. Additionally, the same data was being entered multiple times into different tools. Staff was frustrated with the inability to measure progress against goals. Plaster Group’s Enterprise Software team was asked to assess build vs. buy software solution options for managing our client’s strategic objectives.


Plaster Group engaged a cross-functional team of FTEs and 3rd party providers at the client to develop an assessment of several build vs. buy software solution options. The timeframe for development was short due to critical business process driven deadlines. However, the Packaged & Custom Delivery team was able to coordinate and negotiate costs, resources, and establish a solution blueprint that would ensure the client’s next set of goals would be managed within a single point solution that met the business’ needs.


The solution leveraged tools and skillsets that the customer already had in-house.

  • Web UI allowing data capture and viewing of organizational goals and progress
  •  Integration of existing domain data to maintain organizational data quality
  • Filtering options and excel export features to support data manipulation tasks
  • Reporting options to allow monitoring or results over time


A single web-based tool, simple in both design and interface, now allows staff, working across matrixed teams, to collect, record, and report measured progress against shared priorities and goals.

Which Microsoft Dynamics Solution is the Best Fit for your business?

Microsoft Dynamics is a series of Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) applications with more than 350,000 customers. It consists of four products:

  • Microsoft Dynamics AX
  • Microsoft Dynamics NAV
  • Microsoft Dynamics GP
  • Microsoft Dynamics SL

With varying capabilities, which of these products is the best fit for your business? Here’s a quick guide to the differences between Microsoft’s ERP products.

Microsoft Dynamics AX

Microsoft Dynamics AX, the fastest growing of the four Dynamics applications, is a multi-language, multi-currency ERP business application. A best fit for organizations with multi-country operations, it supports industry-specific and operational processes across global enterprises. Keep in mind Microsoft Dynamics AX is a heavy-weight solution: it takes longer to implement than the other three Dynamics applications, has the most expensive license, and requires full-time development resources to implement.

Microsoft Dynamics NAV

The biggest seller of Microsoft’s ERP solutions, Microsoft Dynamics NAV is inexpensive to implement and maintain. It is highly customizable with a wide-range of add-ons. This is a great fit for mid-sized businesses that are global but do not yet have a complex organizational structure. Dynamics NAV can provide your mid-sized business with the powerful technology to compete with larger organizations, and will grow alongside your company.

Microsoft Dynamics GP

The second most popular of Microsoft’s ERP solutions, Dynamics GP’s out-of-the box business management functionalities include financials, human capital management, and manufacturing operations. It is a great fit for small and mid-sized business in the professional, financial, or public sectors.

Microsoft Dynamics SL

Microsoft Dynamics SL is designed for small, project-driven organizations. This is a niche product that is best suited for companies with less than 500 employees. It provides project, service, and distribution-driven businesses with functions to improve the profitability and efficiency. Its functions include finance, project accounting, manufacturing, supply chain management, and ecommerce.

Plaster Group is a Seattle-based business management consulting firm that includes Microsoft Dynamics Consulting. Read more about the difference between Microsoft Dynamic’s products, and find out our business consultants can help you choose, implement, and maintain your ERP solution here.

Here’s another few helpful links:

Custom Business Intelligence Application Development


Our  Seattle-based client began an initiative to improve data access, collaboration, and critical analysis, and to better harvest and aggregate relevant data from external sources – with the aim of eventually integrating this data with internal systems. Additionally, they desired to streamline reporting processes which previously relied on business analysts to gather their own non-standardized data and build custom reports for various business needs. Analysts prepared briefing materials, strategy review, and development while aligning with partners and investors on key indicators and metrics. The client’s goal was to reduce the time spent in collecting and utilizing relevant statistics, leverage previous investments in data collection, reduce repetition of gathering by different stakeholders, and increase consistency in the use of data enterprise wide

Plaster Group’s Data & Analytics team was tasked with providing a Business Intelligence solution to more efficiently compile global statistics and present them to end users via a user friendly graphical interface that supports the ability to view, report, compare, analyze and discuss data. Plaster Group needed to provide a technical solution that would be an easy to use go-to source for trusted data and address the intrinsic difficulty of compiling data from disparate external sources and the inability of our client’s staff to leverage other team’s gathered data. We were also asked to provide an interface capable of giving non-expert users access to the newly standardized data, a set of reporting tools for the production of standardized, cost effective reports and to provide ad-hoc analytical analysis.


Plaster Group deployed a Business Analyst, ETL Platform Developer, and BI Solutions Architect to work with our client’s leadership and product sponsor to identify solution requirements and lead a team of external consultants in the design, development, testing, and deployment of the new solution. Given the complex and changing nature of the solution’s user requirements, Plaster Group elected to use a prototype driven development methodology – getting the tool into user’s hands as swiftly as possible and getting immediate feedback – a practice unfamiliar to our client’s teams and vendors, so methodological advocacy and coaching were critical.


Plaster Group delivered a software solution built on a reusable data warehousing platform capable of being leveraged for the creation of future applications without the need to build new back-end services. This solution provides:

  • Effective External Data Integration – Easy and contextual access to external data, aggregating external data into a central resource without the need for code or schema changes beyond the ETL changes required to import new data
  • External Data Compilation – External data from multiple sources compiled into one interface allowing for simple and efficient comparison of data across all sourcesEmbedded Tableau Reporting Infrastructure – Streamlined production of quality, standardized reports and visual data analysis
  • Dynamically Rendered, Easy to Use Graphical Interface – Rich GUI, dynamically rendered via the metadata attached to indicators was designed to increase general staff exposure to commonly used data. This reduced the need for subject matter expertise in acquiring relevant data and allowed for either ad hoc or structured access to data for a broad range of users
  • Search, Browse, Collect functionality – Reduced time spent collecting relevant data
    • Search – Discover indicators based on specific terms via the user interface or SQL query
    • Browse – Explore the table of contents and filter by geography, date and other dimensions
    • Collect – Users are able to build and persist a named collection of disparate data and metadata to Excel and other tools for analysis


The BI solution was delivered on-time and on budget. The application has since provided its broad user base with streamlined abilities to seek, store, and share the quality, reliable data. This informs their team’s choices about where and how to invest resources and provides the ability to create reports directly from the application. In turn, our client saves time and expense as data is more easily accessed, compiled, shared and re-used by broader employee teams. Quality reports are crafted and delivered swiftly in standardized, easy to consume formats. 

Additionally, all components of the application are coupled loosely, so the resulting modules are re-usable and can be leveraged for future applications. This allows for greater consistency in the design of future solutions and a great deal more institutional knowledge application to application while saving our client additional expense.