Data Analytics is clear results and direction.

Data analytics is the science of analyzing raw data in order to make conclusions about that information. Data analytics techniques can reveal trends and metrics that would otherwise be lost in the mass of information. This information can then be used to optimize processes to increase the overall efficiency of a business or system.

Data analytics is a broad term that encompasses many diverse types of data analysis. Any type of information can be subjected to data analytics techniques to get insight that can be used to improve things.

For example, manufacturing companies often record the runtime, downtime, and work queue for various machines and then analyze the data to better plan the workloads, so the machines operate closer to peak capacity.

Why Data Analytics Matters

Data analytics is important because it helps businesses optimize their performances. Implementing it into the business model means companies can help reduce costs by identifying more efficient ways of doing business and by storing large amounts of data.

A company can also use data analytics to make better business decisions and help analyze customer trends and satisfaction, which can lead to new—and better—products and services. 

How is Data used?

Data analytics can do much more than point out bottlenecks in production. Gaming companies use data analytics to set reward schedules for players that keep most or the majority of players active in the game. Content companies use many of the same data analytics to keep you clicking, watching, or re-organizing content to get another view or another click.

The process involved in data analysis involves several different steps:

·        The first step is grouping or categorizing the data. Data may be separated by age, demographic, income, or gender. Data values may be numerical or be divided by category.

·        The next step in data analytics is the process of assembling or collecting the data and the means of storage. This can be done through a variety of sources such as computers, online sources, cameras, environmental sources, or through personnel.

• Once the data is collected, it must be organized so it can be analyzed. Organization may take place on a spreadsheet or other form of software that can take statistical data.

• The data is then cleaned up before analysis. This means it is scrubbed and checked to ensure there is no duplication or error, and that it is not incomplete.

The 2 steps above can be described as Database normalization. This is the the process of structuring a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. This step helps correct any errors before it goes on to a data analyst to be analyzed.

Types of Data Analytics

Data analytics is broken down into four basic types.

1. Descriptive analytics describes what has happened over a given period of time. Have the number of views gone up? Are sales stronger this month than last?

2. Diagnostic analytics focuses more on why something happened. This involves more diverse data inputs and a bit of hypothesizing. Did the weather affect beer sales? Did that latest marketing campaign impact sales?

3. Predictive analytics moves to what is likely going to happen in the near term. What happened to sales the last time we had a hot summer? How many weather models predict a hot summer this year?

4. Prescriptive analytics suggests a course of action. If the likelihood of a hot summer is measured as an average of these five weather models is above 58%, we should add an evening shift to the brewery and rent an additional tank to increase output.

Bottom Line is, you can’t manage what you can’t measure.

If you aren’t properly measuring something—whether it's your weight or the number of defects per million in a production line—it is nearly impossible to optimize it.

EIS is your 1 stop shop for Data Analytics and Business Intelligence. EIS IT Consulting can gather, organize, and present your data in ways you have never seen before. Contacts us at 440-918-0140 or consultEIS@gotoeis.com. EIS is a Microsoft Gold Partner – Data Analytics.

Cloud Productivity can be realized!

At the heart of Digital Transformation is the utilization of cloud computing and collaborative productivity tools. Microsoft has re-invented itself from running software on PCs to a cloud computing powerhouse, and it is the most widely used enterprise cloud service today. The Microsoft tools have become more mobile and more collaborative and are enablers in the speed and reliability of Digital Transformation .  

Eight years after launch, Microsoft’s Office 365 is the most popular enterprise cloud service. It's estimated that one of every five corporate employees (20 percent) use an Office 365 cloud service. In fact, Office 365 has 155 million active users, which is doubled from 2017.

Office 365 provides the latest version of Word, Excel, PowerPoint, Outlook, OneNote, Publisher, SharePoint, OneDrive and Skype for Business, and Access. The main reasons enterprise and SMBs alike have moved to Office 365 are Anytime - Anywhere Access, Security, and Reliability.  Office 365 also comes in several flavors or versions. The highest versions of Office 365 which now has versions that are named Microsoft 365, are already available and have office productivity tools that can be managed and shared between users.  The newest and highest-level versions of Microsoft 365 contain the newest features of Anti-threat Protection, Mobile Device Management(MDM), and phone capabilities. Side note, we have rolled out MDM and it works well for all types of devices and remote users.     

These new features of subscription-based software Office 365 are also can collaborate with the newest productivity tools that come bundled in the versions that most users are not aware of right now. Microsoft SharePoint, Teams, Video, Yammer and Delve are included in almost all versions of the product. Teams which has absorbed the Skype for Business functionality is quickly becoming a very important tool for all businesses and has proven productivity gains as noted at the Microsoft Inspire event. Teams is also being groomed to interface with Telephone systems.  OneDrive for business is recognized and widely used as almost all subscribers have started to use the cloud storage in some manner and is utilized as the main file storage mechanism for the tools and features alike. SharePoint Online has become a focus of Microsoft and supporting the other services such as 365 Groups, Teams, and Planner – all collaborative tools designed to improve productivity.  

If you are running your business on local machines, want to improve or re-invent your business, or get caught up on digital transformation and how it can benefit you -  call an expert – Call EIS!  

Contact us to learn more about Microsoft 365 and its tools to make better use of your Time, Talent, and Treasure

Call or contact EIS at 440-918-1040 or ConsultEIS@gotoeis.com.   

IT Resume Writing Tip #1

IT Resume Writing Tip #1 – Professional Summary

A well written IT professional summary can be key to finding your next great opportunity by setting yourself apart from those you are competing against for a particular role. 

A professional summary should be:

·         Be brief – 3 to 4 sentences

·         Include specific details who you are and what technologies (C#, Angular, Java) or skills (Project Management, Business Analysis, Systems Administration) you can demonstrate or have performed

·         Should be written for the specific job you are applying for

·         Use the language the job uses to describe yourself

·         Can include a relevant example(s) of what you have accomplished that articulates you are a match to the position

For more information on how to write an excellent IT professional summary and IT resume feel free to contact EIS at ConsultEIS@gotoeis.com  

Personally Identifiable Information or PII

Protecting PII?

Personally identifiable information (PII) is any data that could potentially identify a specific individual. Any information that can be used to distinguish one person from another and can be used for de-anonymizing anonymous data can be considered PII.

Personally Identifiable Information (PII), is considered as any information that can be used to distinguish or trace to an individual’s identity.

Examples include:

• Name

• Social Security Number (SSN)

• Passport number

• Driver’s license number

• Financial account and personal identification numbers (PINs)

• Street or e-mail address

• Phone number

• Associated data –data that when alone may not be able to identify an individual but when associated with other data leads to identification (e.g. IP addresses, groups or associations)

Today more than ever it is extremely important for organizations to protect their personally identifiable information (PII). Knowing WHAT (above), WHEN, and WHERE you have PII is extremely important for organizations today. PII data must be treated and identified on its own in order to comply with the guidelines and provide the protection required. 

Organizations need to know the thresholds of WHEN PII enters and exits the data and company boundaries. Organizations should get into a habit of periodically reviewing and auditing their environment for PII. PII can also exists in several different forms - employee PII, as customer PII, created, received, or maintained, and business partners PII. An organization needs to determine the flow of the PII as it enters and WHERE it is recorded/stored to ensure its security and confidentiality.

Organizations need to know the laws and contractual obligation requirements for protecting PII data. It’s very important for organizations to be aware of any laws or contractual obligations that are required to protect PII. Commonly known laws and obligations we are familiar with include: the Health Insurance Portability and Accountability Act (HIPAA) and Gramm-Leach Bliley (GLB). There are State and Local Laws are to be equally considered for the management of PII, and additionally other laws and guidelines pertaining to an organizations industry as well.

What should you do to be and remain safe?

Perform a PII Risk Assessment (Assess all data). Risk assessments should be performed at least on an annual basis.

A central component of many privacy compliance standards and regulations is the performance of a risk assessment. This not only serves as the basis for compliance with the various compliance and reporting efforts but is also essential for good corporate governance. In the context of safeguarding PII, this risk assessment should provide specific coverage over the at least the following:

• Identification of regulated PII

• Identification of other sensitive data

• Identification applicable laws and regulations described earlier

• Determine threats to compliance with the external and internal processes

• Risk management strategies

  • Identify avoidance, sharing and common practices

  • Define the control procedures for handling and securing all data

·         Ensure all internal and external stakeholders and partners are involved, understand the requirements, and are kept informed of any practices and policies

Create safeguards for protecting PII according to Confidentiality and Privacy impact

Organizations should create safeguards according the risk assessment (as described earlier) and confidentiality and privacy impact associated with the PII data. These safeguards should clearly reflect the organization’s risk mitigation strategy and be evaluated on a periodic basis for design and operational effectiveness and be revised accordingly. Listed below are a few safeguards that organizations can utilize:

·         Categorize Data and PII. Some data may be less risky to collect and retain than others - email address vs social security numbers

o    Only collect and retain PII that is necessary to perform the business function related to its collection

• Create policies and procedures – organizations should have policies for the collection, use, retention, disclosure and destruction of PII and all organizational data to include but not limited to (email, meeting notes, documents, bills, etc.). A periodic review of Records Retention and a company standard should be established for the organization. These policies should be adopted and communicated to employees.

• Training – organizations should train their employees how to protect and handle PII to reduce the likelihood of a incident or breach.

• Archive Practices – organizations can protect PII and all data by archiving and removing it where it may no longer be needed. These practices can be defined in conjunction with the Records Retention standards for an organization.

• Encryption – organizations can encrypt databases and repositories where PII is stored.

Contact us to learn more about securing data can provide you benefits and make better use of your Time, Talent, and Treasure.  Call or contact EIS at 440-918-1040 or ConsultEIS@gotoeis.com.