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5 ways companies are using big data to help their customers (via VentureBeat)

big data, enterprise data, analytics, data analytics, data modeling, data science, data modeling, data model, data, data science, data scientist, data management,

Five ways companies are using big data to treat customers more like individuals — and build better long-term relationships so those customers happily buy more and more

Source: VentureBeat

Review

As we all remember, back in the day you could go to the store and the clerk would know you personally.  They would ask you how you are and how your family is. It was a very personal relationship you would have, therefore creating loyalty between you and the store.  It has been lost for a while when stores started to sell online.  There were no programs to make your shopping experience more personal or enjoyable.  You just went online to search and buy.  Big data helps to build relationships again as it can help companies offer better service to customers if used.   Here are the five ways that big data helps online stores to treat their customers more like people instead of just numbers.

5 Methods to Use Big Data

  1. Prediction – Big data can help analyze past behaviors of customers to build a more personalized experience for them. This in turn creates satisfaction for the person and increases purchases.
  2. Excitement – This is more for wearable technology. FitBit and other companies spew out the data they gather to their clients, which makes the client more interested and excited to see improvements.  This is completed in other industries too, not just the health industry.  There are apps to help track finances too and make people excited to invest more.  Showing the data makes the client happier.  It can show them where they need to work to improve themselves too.  It’s a good tool for the customer to use.
  3. Improvement – Customer service is just as important as effective marketing and product development. Big data can help in all these areas too.  Representatives can answer questions more quickly and effectively when the correct data is in front of them.  This way the customer doesn’t feel like they are being badgered.  The data helps as the customer has so many ways to get a hold of companies now than before.
  4. Identify – Find the difficulties customers are having to improve their experience. It’ll make for happier and more loyal customers.
  5. Reduce – This deals with the health care industry for improving quality of patient care. It helps to cut cost and improve treatments.

Summary

Big data helps companies now to understand their customers better.  This helps agencies give better services and build relationships again, in a more modern way.  Just consider all the possibilities.  I would think about switching over myself if I had a bigger company and could afford it.

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84% Of Enterprises See Big Data Analytics Changing Their Industries’ Competitive Landscapes In The Next Year (via Forbes)

big data, data science, big data analytics, analytics, data modeling, data management, smart data, data mining

87% of enterprises believe Big Data analytics will redefine the competitive landscape of their industries within the next three years. 89% believe that companies that do not adopt a Big Data analytics strategy in the next year risk losing market share and momentum. These and other key findings are from an […]

Source: Forbes

I just thought that I would share this article.  It has some great statistics on why Big Data is now considered essential for any type of competitive growth.  For example, only 13% use Big Data analytics in predictive modeling, while only 16% are using the information that they find to improve processes.  If you were to use Big Data analytics, image what kind of growth your business could have…

I love studies as they always show the numbers to help strengthen their arguments.  Just wanted to share this with you all.

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Steps to create Data Model (via learndatamodeling.com)

Big Data, big data, data modeling, data, data science, data scientist, data management, analysis, data analyzing, technology, tech

Source: learndatamodeling.com

Review of Article

These is general guidance for creating standard data models.  I’m not going to include all the steps as it’s over 24 separate steps, but depending on what your business requires you might not need to have all the steps anyways.  The link to the article is above if you’d like to see the entire list of what you can include.

Steps for Building Logical Data Models

  1. Gather up the business requirements
  2. Analyze business requirements
  3. Select target database – the data modeling tool will build the scripts to create reports
  4. Assign data type to attributes created to find data
  5. When analysis complete create columns to sort data
  6. Build subject areas to add the data
  7. Validate data model
  8. Create reports

Steps for Building Physical Data Models

  1. Get the logical data model and build a physical one from it
  2. Add properties to sort data
  3. Create SQL scripts
  4. Compare the database from the data model
  5. Create change log to document changes that have occurred

 

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Data Modeling Trends in 2018 – DATAVERSITY (via DATAVERSITY)

data modeling, data science, data scientist, data, data security, ai, machine learning, deep learning, big data, Big Data, enterprise data, data management, internet of things, iot, smart data

The Database Management and Data Modeling landscapes have evolved much in the past few years, from the traditional relational model to now include non-relational models as well.

Source: DATAVERSITY

Review of Article

Advantages of Data Modeling

  1. Provides clear framework for development projects
  2. Enables high performance
  3. Corrupt datasets are found quickly and cleaned before using
  4. Offers tested models for building software
  5. Outlines scope and risks during development
  6. Includes detailed documentation which helps with future maintenance

New Trends

  • Wide variety of machine facts to include Internet of Things (IoT)
  • Scale and speed of data increasing along by machine learning
  • Demand of aggregated data is increasing
  • Public, private on-site Cloud storage
  • Huge amounts of data collected into what is Data Lakes (unchanged data) for data scientists to analyze later
  • Automated data modeling (algorithms)
  • Predictive modeling with advanced machine learning
  • Semantic data models

SQL Database Trends 2018

  • Adoption rates will differ as companies due to security concerns
  • Cloud adoption
  • AI capabilities are increasing
  • SQL Servers for Linux
  • There are new schedules for software updates (handled by the vendors themselves, not Microsoft like before)
  • Use of Data Vaults

Summary

It sounds pretty exciting doesn’t it?  So many changes to look forward to trying out for your business.

 

 

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3 Challenges to Business Intelligence and Analytics Adoption

big data, challenges, business intelligence, BI, analytics

Business Intelligence and Analytics

What is the biggest challenge today for upgrading your business? You’ll find the answer through using tools enabling business intelligence (BI) and analytics strategies. It seems that businesses are looking to adopt BI and more advanced analytics to achieve bigger gains. Upper management needs to explore more information to gather key areas that they feel need improvement.

The Biggest Challenges:

  • Data Preparation – The ability to complete data management in putting together and cleaning data before compiling reports and analytics.
  • Skills and Leadership – Is there a structure focused on needs of both BI and analytics along with more complex methods?
  • Ease of Use – Can those who are less technically inclined be able to use the system?

Preparing Data

The biggest gaps are in data prep. It is more difficult and more complex than it seems. The size of the company and how they are using BI and analytics doesn’t matter. They all see big gaps in how they filter, transform and prepare their data. Good data gathering and compiling is completed. It helps find both relationships and potential outcomes quickly. The information found here will help improve your company’s productivity and build competitive advantages. Consider automation and self-service also for those in the agency who are less technically inclined. Analytics are behind BI. Improvements are needed to be able to prepare, augment and explore the data gathered. This will help your agency to find root causes and trends. You can then build and update predictive models through using machine learning.

Skills and Leadership

Skills and leadership are key too. Agencies strong in these areas still say that there are many challenges in innovation, creativity, and leadership. Shown executive support enforces the need for upgrades or change just will not happen. If there’s no strong vision and support at this level, the initiatives will fail or underperform. A leader needs to make sure that they openly show the value of success from the new initiatives.

Ease of Use

Overworked data scientists or analysts already in your company because of changes being implemented need help. In this case, it’s better to create self-service and interactive tools where everyone can find them. Nontechnical users will need the guidance, and instead of overworking your data scientists and analysts, this can help. There’s software built to aid building systems that can detect relationships, correlations, segments, and outliers. It could use natural language to create queries. It could present context-based narratives of important findings. All sorts of things could be created with the new software to help the organization.

Increasing adoption of BI and Analytics

  • Invest in data and data prep
  • Nurture culture, skills, and leadership
  • Keep self-service and Ease of Use in the Forefront

Conclusion

If the challenges of gathering and preparing data are not addressed, it will become more difficult to find a use for BI and analytics. If strong leadership isn’t used to make the employees excited to use the new technologies, the initiative will be a failure. And if ease of use with smart/automated capabilities isn’t used, it’ll hinder adoption of BI and more advanced analytics. Consider these things before upgrading your systems.

 

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What is Unit Oriented Architecture?

system architecture, computer architecture, system, UOA, unit oriented architecture, systems,

Definition of UOA

UOA is an business method of performing tasks based on the hierarchical composition of different units of software. These units give support to both operational and actions completed in technological systems. UOA creates groups of software fully supporting purpose, function, behavior, and structure of these systems. It helps clarify and strengthen architectures through finding right places and owners for assets. Included are web applications, mobile apps, web services and business processes to name a few. The unit then becomes both a construct and micro-platform that allows other components plugin.

Key Points of UOA

  • Creates digital constructs for actions completed and operational support
  • Views companies as a Composite (control) or Leaf (functional)
  • Unit software has to be comfortable and work in the unit assigned
  • Every unit has to have formal software boundaries. They represent contracts between assemblies both in and out of the agency.
  • All units have to run operations implemented as business processes that are executable. Every process is owned by one section only.
  • There is particular emphasis on control units. It causes a weakness in the company as only a few personnel will know how to run it.

What Does UOA Do?

UOA uses Systems Thinking to define problems. It uses Organization Design to configure enterprise and composite units. SOA uses constructing unit boundaries, and Business Rules to govern the system to name a few.

UOA allows practical and natural approaches to satisfy the needs of users. It completes this through unit orientation and clarity of what the system is supposed to do. Hierarchical unit structure helps define roles and spreads responsibilities between all the units. It creates a stable system where it can adapt, develop and grow fast. Process-centric (inside) and event-driven integration (outside) is where processes pass through the units to complete work.

Differentiation between functional and control units is defined here. Functional (leaf) units don’t contain other groups. They provide services and products, all digital. Control units have more entities in them. Actions are directed, coordinated, measured and controlled to ensure best means to get the bottom line. There’s a clear understanding of what everyone is to do in the company and delegates decision making to the right people.

Supported are operations interactions. The direction of vision focuses towards products and services instead of the process is itself. The quality of communication between system parts is considered more important than the quality of parts. The character of interfaces measures effectiveness.

The Possibilities

If a company’s units support strongly built digital constructs that entirely concentrate on the customer, everything will grow. Effectiveness, efficiency, and efficacy will improve. New capabilities initiate with further development. Growth through cloned abilities will occur, while agility will increase speed. There are numerous opportunities abound.

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Digital Transformation – 5 Identifiers

digital, digital transformation, upgrading systems, upgrading business systems, business systems

What is Digital Transformation?

Numerous changes happen where digital economy of business is connected real-time due to new technologies. Digital transformation is directly related due to this. Just about all small and midsized firms have some sort of resources in place. It can be anything from newer and more powerful software and/or computers, new forms of communication or cloud computing. The company has to ensure good implementation and integration of programs to increase performance. How to do this is:

5 Identifiers

  1. Hyper-connectivity – Anytime/Anywhere communication
  2. Unlimited Computing Power – Caused through diverse platforms
  3. Cloud Computing – Easy access to hosted software/services
  4. Numerous Sensors and Mobile Devices – Supply continuous streams of information and ways to access them
  5. Cybersecurity – Lessen internal/external vulnerabilities

Why Buy At All?

Faster growing companies look at ways to drive revenue growth, increase productivity, and get new customers. This is supported through the use of advanced technology. The question becomes what is the best approach to get and use new technology in order to support objectives? Most are buying advanced software applications to help grow their businesses. Buying collaboration software, CRM and ecommerce all help growing businesses through helping internal productivity and efficiency. When one application is updated, they all are. This improves performance of the agency as a whole.

Causes to Upgrade

Most upgrade due to partner and/or customer needs. Their main focus is to improve internally.  External influence is also taken into consideration though. Who wants to chase away potential clients due to not listening to their needs too? This is key in order to keep up with competition and the environment that they work in. Effective coordination of technology brings in greater performance results.  It is greater then the sum of the parts bought to improve the system as a whole.

Benefits

The departments that benefit the most from these improvements is sales and marketing. Everyone from services to manufacturing to wholesale and retail benefit too. Internal processes is also up there, but externally faced business is considered more important. This is the rank from highest to lowest in importance:

  • Sales
  • Marketing
  • Production / Operations
  • Commerce / Ecommerce
  • Customer Service / Call Center
  • Finance
  • Supply Chain Management
  • Manufacturing
  • Strategic Planning
  • HR

3 Takeaways 

  1. Leverage Technology
  2. Digital transformation is a continuing process
  3. Direct / Continuing participation and support of senior management and executives. If there is none, or it is perceived as none, then changes will be hard to implement.

Key Questions to Ask

Key questions to ask yourself and those involved in the process of beginning the changes are many. Where are you falling short compared to other companies? What is the competition doing that you are not? Do you have a strategic plan in place that supports digital transformation? Some things to consider…

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3 Phases of Business Analysis Verification Testing

test, work, , business analysis, business, complete, system, strategic planning, software

The first thing you should do after buying a product for the business analysis solution is to verify if the software will work with your vision.  Will it do what it is supposed to do?  When it is being verified the testing team who can be anyone from developers, QA and business analysts work with the software to make sure that it really works for what it was bought and/or created for.  There are many phases to be completed in order to ensure the new product will work well with your system.

The Test Phases

The Smoke Test comes before anything.  It’s a pretest to find out if full testing can begin.  This test shows simple failures that could keep further tests from being executed in the next 3 phases.

  1. Unit Test: Here every unit is tested separately to find any possible bugs before moving on.  It’s another name for the smoke test.  Don’t just have the development team test it here, but others to so there will be unbiased testing completed.
  2. Integration Test: This part makes sure that all the individual parts can work together; either as a subsystem or linked units.  Here you would want to find problems with how components will work together in the software architecture design.  This includes multiple levels of integration where subsystems might be brought in to see if they would work, then attached to larger subsystems when in compliance.  The development team and possibly business analysists work here.
  3. System Test: Here is where problems are found with how the new system meets users’ needs.  It’s ran through the entire system, auditing everything from linear perspective’s.  It’s the last chance before turning over to a user acceptance test, and verifies if the software meets original requirements.  The business analyst works here for the most part.

Other Tests to Be Completed

There are numerous other tests that have to be completed during these 3 phases.

  • Requirements validation test: Verifies system logic, making sure that it supports system analysis.
  • Regression Test: Retesting to ensure changes don’t break what is working.  There’s usually more than one test completed to make sure all the applications work.
  • Dynamic Test: Testing of the software in different circumstances.  There are 3 tests completed here:
    • The Performance Test: How fast can the system complete functions?
    • The Stress Test: Push the software to its limits to see how it handles levels of users, rates of input and speed of response.
    • Volume Test: Can the new software handle growth projections?
  • Security Test
  • Installation Test
  • Configuration Test
  • Usability Test

Why Test and a Way To Help Implement

With all these tests completed it will help you to not have problems down the road.  There’s a need to make sure that everything will work before turning it loose for everyone to use in your company or sell online to your customers.  Click here to get an awesome partition assistant from AOMEI to help maximize disk space and improve the performance of your computer(s).  This will be needed when growing your system, implementing new programs and applications.  The best part of this is that it has the Windows to Go Creator which would help immensely in the long run too.

 

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What is the Role of Information Systems in the 21st Century?

information systems, business, IS, business information systems

Whether or not a company wants to believe it, information systems (IS) are a very important part of how the business runs now.  This includes how data is stored, transferred and understood by all the different departments in the agency.  The problem is, it seems that business owners are not really aware of how important IS to their companies in being able to be managed in designated systems.

10 Reasons to Have New Information Systems

10 reasons that it is so important for companies are:

  1. Control Creation and Growth of Records – Less paper wasted as everything becomes computerized
  2. Reduces Operating Costs – Storing inactive records in IS costs less per linear foot for the company
  3. 3. It Improves Both Efficiency and Productivity – Helps to upgrade record keeping so retrieval of information needed is vastly improved
  4. Assimilate New Records Management Technologies – Can be used in any area of the company, helps analyze manual recordkeeping and applied automation
  5. Ensures Regulatory Compliance – Companies have to be able to make sure that they are in regulations by having a good IS that is responsible for regulatory compliances
  6. Minimize Litigation Risk – The main reason IS is used is to reduce the risk of litigation and penalties. A newer system put in place will help to ensure this happens.
  7. Safeguard Vital Information – This is necessary in order to protect records and information as all agencies are susceptible to attack or natural disasters. This will provide backups and save the information in a safe place of the company’s choosing, for retrieval later.
  8. It Helps to Support Better Management Decision Making Capabilities – A newer system put into place will help managers and executives to better find information that they need when they need it to make critical business decisions. ERP systems would be perfect here instead of doing everything manually.
  9. It Helps to Preserve Corporate Memory – This is done through everyday activities and record keeping.
  10. Foster Professionalism in Running the Company – Neatness and cleanliness are key in running a smooth organization

Why Update at All?

Good, solidly built IS  means that companies that use it will be able to align their strategies together into a clear point of view as to where they want to go.  It also helps to find relationships that would be considered critical and gaps in their company culture and infrastructure.  Good information systems  find answers on how to gain competitive advantage against their competition by improving alignment to strategic decision making.

 

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Why All the Different Information Systems?

IS, DSS, EIS, TPS, MIS, information systems, organizations, senior management, junior management, executives, executive decisions, senior management decisions, junior management decisions,

This all started back in the day.  Someone would need a system made specifically for them to handle one problem.  Soon enough that it was discovered that different problems needed similar solutions, but not always in the same manner of getting them.  This is where defining of the information systems began and why it is still needed.   When the company in question decides that they need to upgrade, they have to go through a process in order to find the right applications and hardware to handle their data.  Classification comes to play here, so that categorizing information can be completed correctly.  This will help to make the data one unit instead of many.

How Do You Identify Different Types of Systems?

There is no simple answer to the question.  Every company builds an information system (IS) that is tailored to their specific needs.  There are many different types of IS that are used in some manner or another.  Classifying IS relies on how tasks are performed and responsibilities are divided in the agency.  This becomes a pyramid model as most companies are hierarchical, so classes of IS are categorized following the hierarchy going down.

To compare different information systems:

  1. Transaction Processing Systems (TPS)– These are operational level systems.  They are used by shop floor workers and front line staff.  Data is gained here through tracking of low-level activities and basic transactions.  They function as simple data processing systems only.  This is the system that produces information for other systems to use.  They are used internally and externally, are used by operational personnel and supervisors and are focused on efficiency.  Examples:  Payroll, Order processing, Reservations, Payments and Funds Transfers.
  2. Management Information Systems (MIS) – Management level used by middle managers. This system ensures smooth running of the company for short to medium terms.  Information is given out highly structured and helps managers to evaluate the company’s performance through comparison of outputs.  MIS is built on data given by TPS.  They are based on internal information flow, support structured decisions, but are inflexible with not much analytical ability.  Examples:  Sales Management, Inventory control, Budgeting, Management Reporting, and Personnel.
  3. Decision Support Systems (DSS) – Knowledge based system used by senior managers. They analyze existing structured information, allowing managers to estimate any potential effects on decisions they are thinking of implementing.  These systems are interactive and are used to solve problems.  They can access databases, offer analytical tools, allow simulations to be completed, and can support exchanges of information in the company.  This system can alter and build solutions provided by MIS and TPS, that can create insights plus new information to go off on.  DSS helps to support badly or semi-structured decisions already being built, and have analytical and modeling capacities.  Examples:  Group Decision Support Systems (GDSS), Computer Supported Co-operative work (CSCW), Logistics, and Financial Planning.
  4. Executive Information Systems (EIS) – Strategic level used by executives and senior managers. These systems analyze environments that the company works in, find long-term trends, and plan courses of action.  The information gathered is gathered from internal and external sources, and is weakly structured.  These systems are designed to be able to be used directly by the executives and are user friendly with the ability to be customized to whomever is using it.  EIS gathers and presents data from the MIS or TPS so senior management and executives can see what is going on a make decisions based off what they see.  The people who use this want ease of use and being able to predict what will happen to the company in the future.  It has to be effective, flexible, and support unstructured decisions.  Examples:  There are none.  These systems are tailored to individual wants of the user, in other words are custom made.  There are off the shelf packages that can be customized too.

The Importance of Planning

There is no easy way to explain why there are so many different types of information systems.  Every company out there is not the same, or runs their agency in the same manner as others.  This is why modifications are made to the systems in order for them to work specifically with what said company uses and the data they keep.  Also every level of the agency uses different systems.  Not everyone has to have a need to know of everything going on.  It is better to keep it at the level that the systems are going to be used at the most.  This is why planning for upgrades is so important.  If the wrong system is used, or the wrong programs…