Table of Contents I. Introduction …
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…2 II. Problematic definition .
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…2 III. Research Questions Formulation and Possible Solutions .
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….2 IV. Background ..
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….2 a. Data Storage .
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…………….. 2 1. Block storage ……………………………………………………………………………………………………………………. 2 2. Object storage …………………………………………………………………………………………………………………… 3 3. Database storage ……………………………………………………………………………………………………………… 4 4. Archive storage …………………………………………………………………………………………………………………. 4 b. Categories of Companies ………………………………………………………………………………………………………….. 4 V. Chapter 1: Classification of Data ………………………………………………………………………………….5 a. Needed Of Data Classification …………………………………………………………………………………………………… 5 b. Stages Of Data Classifications …………………………………………………………………………………………………… 6 1. Stage 1: Establish goals & Perspectives ………………………………………………………………………………….. 6 2. Stage 2: Diagram: Classes and Rules ………………………………………………………………………………………. 7 c. Relational Data and Non-Relational Data……………………………………………………………………………………. 8 d. Structured and None-Structured Data ……………………………………………………………………………………….. 8 VI. Chapter 2: Influential Business Factors for Selection the Solution ………………………………………8 a. Data Usage …………………………………………………………………………………………………………………………….. 8 b. Budget …………………………………………………………………………………………………………………………………… 8 c. Knowledge ……………………………………………………………………………………………………………………………… 8 d. Timing ……………………………………………………………………………………………………………………………………. 8 e. Impact ……………………………………………………………………………………………………………………………………. 8 f. Alignment ………………………………………………………………………………………………………………………………. 8 VII. Chapter 3: Requirements and Selected Solutions ……………………………………………………………8 a. Data Storage Solutions …………………………………………………………………………………………………………….. 8 1. Data Center Solution “Private Cloud” …………………………………………………………………………………….. 8 2. Cloud Solutions “Public Cloud” ……………………………………………………………………………………………… 8 3. Hybrid storage Solution………………………………………………………………………………………………………… 8 b. Match with Requirements ………………………………………………………………………………………………………… 8 c. Model Select Solution ……………………………………………………………………………………………………………… 8VIII. Chapter 4: Implementation Phase ……………………………………………………………………………….8 a. Case choosing storage solution to Nokia Bell Labs “My Team” ……………………………………………………… 8 I. Introduction II. Problematic definition III. Research Questions Formulation and Possible Solutions IV. Background a. Data Storage The needs of electronic storage still grow as still enterprises produce more information in electronic formats which increasingly important the needs of storage space. Data storage is a term for how to keep the information in a digital format to be able to retrieve it at a later time. Computers, laptops, tablets, smartphones, and other devices all store data. Methods and technologies used vary greatly, but the basic concept is always the same: information is kept so that it can be used and accessed again whenever we want. Basically, there are three different methods of data storage Object, DataBase(DB) and Archive Storage. Each of these storage methods has its own requirements in terms of performance, scalability, availability and price. 1. Block storage Block storage is data storage typically used in Storage-Area Network (SAN) environments where data is stored as blocks in volumes. Each block is assigned an arbitrary identifier by which it can be stored and retrieved, there is no metadataproviding. Database storage is a common use for block storage. Blocks are acting individua as “hard drive” controlled by server-based Operating System(OS) and accessed by cables either RG45 which is Ethernet Protocols or Fiber Optic Channel, where are configured by the administrator. Block storage works for storing a variety of applications. There are two common uses for block storage are File Systems(FS) and DataBases(DB) because they require consistently high performance. Nowadays almost companies are using RAID arrays are a prime use case for block storage. RAID used multiple independent disks combined for data performance and protection. RAID get a benefits of block storage to create individually controlled storage volumes. As will Virtual Machine(VM) file system took an advantages of block storage by used it, such as VMware vendors support block storage protocols to improve scalability and migration performance. While there are benefits to using block storage, in the same time there are alternatives depends of organizations needs or uses. Two options stand out when it comes to facing off are: DataBase storage and object storage. 2. Object storage Object Storage is data storage solution based on storing of files in a storage system where that files are accessed through an Application Programming Interface (API). Basically, files systems are known by a unique identifier instead of a location on a disk. Object storage used the same method of block storage to be accessed to the files where are located in logical disk in SAN. The main difference is that object storage used Distributed File System (DFS) method and Files are combination of Data and Metadata.3. Database storage DataBase storage conduct on data already stored in structured files according to specific format or schema. Which is the different from Object storage system where the structured file doesn’t change any of it storage process. DataBase storage offered high integrity and consistency properties plus powerful Ad-hoc querying functionality. Nowadays Set of ACID (Atomicity, Consistency, Isolation, Durability) properties well known for database transaction. DataBase have two system relational database and non-relational database we will have full description in Chapter 1 Classification of Data. 4. Archive storage Archive storage is to turn data from active state into inactive. Archive storage method depends on different requirements either than Block, Object and DataBase storage. Since access to the archive shouldn’t be regular, so there is no need for accessible data in milliseconds. Thus, archiving data into separate optical disks, tapes or off-line media. The choice for storing depends on longer expected lifetime and secure environment because the main reason of archive storage is business growth generate more data that could be retrieve in certain time for some improvements or other reasons. b. Categories of Companies We categorized companies into three types which are Small, Medium and Big according to its number of employees. These types obtained according the size of each company in different countries. Nowadays there are different types of business according to these types. We can see many companies specialize in Healthcare, Telecommunications, Marketing, Banking, Constriction, Management, Security, Industries, Consulting, Food, Entertainments or Media. In addition, there are some companies have a group which contain all this kind of business.Small Medium Large EU Countries 10-49 50-249 250 + United State 10-99 100-499 500 + Canada 10-49 50-499 500 + Others 10-49 20-200 more less 150 + Source: OECD According to these different types of companies and their data classifications, we will recommend their needs of different types of data storage solutions. V. Chapter 1: Classification of Data The concept of data classification is a process allow us to define a data and categories it in groups. All companies made data classification to create compressive storage strategy which is allow to categories the data depends on business priority. Data classification help us to define key storage solutions. For example, maintained data on its appropriate storage infrastructure or make a consolidation between data in this case we need to classify data depends on location and physical state. In addition, to understand the day to day value of data operations in any business and how fast it needs to be accessed and by whom. All these properties motivated us to use data classification to help us in in this research. a. Needed Of Data Classification In bigger picture as we said before in “Categories of Companies section” the different types of companies and their business they have a most important asset common whichis data. Therefore, companies they work with this data and they know how to do analysis and took decision depends on it, but not all of them they know what it is exactly, because data not same in all fields. So that derive us to light on this problem which is lead us to the critical point which is how is data stored and where. In simple way what is the data storage solution will provide us the best performance to work and save our data depends on data types and our business needs. The resulting of data classification will facilitate and involve our process it choose the best data storage solutions for companies. b. Stages Of Data Classifications 1. Stage 1: Establish goals & Perspectives The First step of the Data Classification processes is establishing a clear storage related goal. It’s like a strategy of any company starting by defining the global goal, in data classification we must do the same role. This may seem like an easy exercise but defining a data classification goal very important because it the result it will produce a model and an actionable framework that could be used to drive implementation plans and strategy for choosing the right storage solution for the company in general. The Second step is the perspective which is the horizontal view of the company’s data. Perspective will help the activities of data classification to produce an important actionable result, where the most famous perspective is the application’s perspective. These applications it will build by the company where the most data could be used to it. Basically, we will address what storage solution should in terms of data to be stored depends on business needs. In addition, perspectives contain the business object, the logical state and physical state. The business perspective is useful for tying business goals and impact on data storage solution selection depending on a critical business function. A business object perspective based on business object or data logical entities within the company. This perspective useful when combining separate data storageinfrastructure from different companies by sharing business priorate and infrastructure requirements to accomplish an economic union of data storage infrastructure and business goals. A logical state perspective provides a framework for data classification based on how it is used and managed within the company. This perspective useful when the more precise classification of data needs to ensure the most powerful of data lifecycle applied within the data storage, for example when we start a project with an application we need to define data type, data content, organization and access method into data storage solution. A physical state perspective provides an information for classifying data based on exacting attributes of data itself. For example, types of media, it used, type of server used for storage and the location of data etc… Finally, by selecting the perspective, we will obtain the classification of data depends on business priority and how it could be used within the company which aligns with the business needs for selecting the data storage solution. 2. Stage 2: Diagram: Classes and Rules Once we finish selecting the perspective, we are ready to draw the diagram which is contain classes and rules. The diagram will provide us segments of the view of the data in the company. In addition, will define the appropriate data matching with the business objective of choosing the data storage solution. To classify data, we must be able to establish what make this data valuable for the company. For example, the (frequency of access). In this step, we will select classes and name it based on business objectives. For example, after we finish the phase of perspective and establishing goal we are ready to select classes depends in our business objectives like “critical business data and non-critical business data” where are defined by availability and collecting time. Finally, the rules will break up the chosen diagram into more narrowly defined categories that will provide direction and drive to choose the company objective which is the data storage solution. Interview and questionnaires to gather of detailed informationfrom stakeholders, managers, and users are the basic essential to creating a viable data classification model. c. Relational Data and Non-Relational Data d. Structured and None-Structured Data VI. Chapter 2: Influential Business Factors for Selection the Solution a. Data Usage b. Budget c. Knowledge d. Timing e. Impact f. Alignment VII. Chapter 3: Requirements and Selected Solutions a. Data Storage Solutions 1. Data Center Solution “Private Cloud” 2. Cloud Solutions “Public Cloud” 3. Hybrid storage Solution b. Match with Requirements c. Model Select Solution VIII. Chapter 4: Implementation Phase a. Case choosing storage solution to Nokia Bell Labs “My Team”
