Module 7: Current Trends in Database Management Systems PDF

MODULE 7: CURRENT TRENDS IN DATABASE MANAGEMENT SYSTEM Module 9: Data Analytics  Data Analytics What is Data Analytics? The term data analytics refers to the process of examining datasets to draw conclusions about the inf...

MODULE 7: CURRENT TRENDS IN DATABASE MANAGEMENT SYSTEM Module 9: Data Analytics  Data Analytics What is Data Analytics? The term data analytics refers to the process of examining datasets to draw conclusions about the information they contain. Data analytic techniques enable you to take raw data and uncover patterns to extract valuable insights from it.  Why is Data Analytics Important? Data analytics is important because it helps businesses optimize their performances. Implementing it into the business model means companies Loading… can help reduce costs by identifying more efficient ways of doing business. 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.  What is the role of data analytics? Data analytics helps individuals and Me organizations make sense of data. Data analysts typically analyze raw data for insights and trends. They use various tools and techniques to help organizations make decisions and succeed.  Four Types of Data Analysis Descriptive Analysis Diagnostic Analysis After asking the main question of “what The first type of data analysis is happened”, the next step is to dive deeper descriptive analysis. It is at the Loading… and ask why did it happen? This is where foundation of all data insight. It is the diagnostic analysis comes in. simplest and most common use of Diagnostic analysis takes the insights data in business today. found from descriptive analytics and drills Descriptive analysis answers the down to find the causes of those outcomes. “what happened” by summarizing Organizations make use of this type of past data, usually in the form of analytics as it creates more connections dashboards. between data and identifies patterns of behavior.  Four Types of Data Analysis Predictive Analysis Prescriptive Analysis Predictive analysis attempts to answer the question The final type of data analysis is the most “what is likely to happen”. This type of analytics sought after, but few organizations are truly utilizes previous data to make predictions about equipped to perform it. future outcomes. Prescriptive analysis is the frontier of data This type of analysis is another step up from the analysis, combining the insight from all descriptive and diagnostic analyses. Predictive analysis uses the data we have summarized to make previous analyses to determine the course of logical predictions of the outcomes of events. action to take in a current problem or This analysis relies on statistical modeling, which decision. requires added technology and manpower to Prescriptive analysis utilizes state of the art forecast. technology and data practices. It is a huge It is also important to understand that forecasting is organizational commitment and companies only an estimate; the accuracy of predictions relies must be sure that they are ready and willing on quality and detailed data. to put forth the effort and resources.  What are Analytics Tools? Top 10 Data Analytics Tools Business analytics tools 1. R Programming are types of application 2. Tableau Public software that retrieve data 3. Python from one or more business 4. SAS (Statistical Analysis System) systems and combine it in a 5. Apache Spark repository, such as a data 6. Microsoft Excel warehouse, to be reviewed 7. Rapid Miner and analyzed. 8. KNIME 9. QlikView 10. Splunk https://www.proschoolonline.com/blog/top-10-data- analytics-tools  6 TRENDS IN DATABASE Databases that bridge SQL/NoSQL MANAGEMENT Databases in the cloud/Platform as a Service Automated Management An increased focus on security In-memory databases Big Data  Loading… Databases that bridge SQL/NoSQL  Databases that bridge SQL/NoSQL The latest trends in database products are those that don’t simply embrace a single database structure. Instead, the databases bridge SQL and NoSQL, giving users the best capabilities offered by both. This includes products that allow users to access a NoSQL database in the same way as a relational database, for example.  Databases in the cloud/Platform as a Service Loading…  Databases in the cloud/Platform as a Service As developers continue pushing their enterprises to the cloud, organizations are carefully weighing the trade-offs associated with public versus private. Developers are also determining how to combine cloud services with existing applications and infrastructure. Providers of cloud service offer many options to database administrators. Making the move towards the cloud doesn’t mean changing organizational priorities, but finding products and services that help your group meet its goals Automated Management  Automated Management Automating database management is another emerging trend. The set of such techniques and tools intend to simplify maintenance, patching, provisioning, updates and upgrades — even project workflow. However, the trend may have limited usefulness since database management frequently needs human intervention.  An increased focus on security While not exactly a trend given the Database administrators must also constant focus on data security, recent work with the security team to ongoing retail database breaches eliminate potential internal among US-based organizations show weaknesses that could make data with ample clarity the importance for vulnerable. These could include database administrators to work issues related to network privileges, together with their IT security even hardware or software colleagues to ensure all enterprise misconfigurations that could be data remains safe. Any organization misused, resulting in data leaks. that stores data is vulnerable.  In-Memory Databases Within the data warehousing community there are similar questions about columnar versus row-based relational tables; the rise of in- memory databases, the use of flash or solid-state disks (which also applies within transaction processing), clustered versus no-clustered solutions and so on.  In-Memory Databases To make the long story short, an in-memory database is a database that keeps the whole dataset in RAM. What does that mean? Loading… It means that each time you query a database or update data in a database, you only access the main memory. So, there’s no disk involved into these operations. And this is good, because the main memory is way faster than any disk. A good example of such a database is Memcached. Big Data  Big Data To be clear, big data does not necessarily mean lots of data. What it really refers to is the ability to process any type of data: what is typically referred to as semi-structured and unstructured data as well as structured data. Current thinking is that these will typically live alongside conventional solutions as separate technologies, at least in large organizations, but this will not always be the case.  What is MongoDB? MongoDB is a non-relational database system. There are two primary database MongoDB was created in 2009 as an open- types: SQL (relational) and NoSQL (non- source, highly scalable, robust, and free relational). Relational databases store data in NoSQL database. It also has a commercial columns and rows. Organizations like version. You can find MongoDB’s source Microsoft SQL Server Oracle and Sybase use code on GitHub. the relational database management system MongoDB has cultivated a reputation as a (RDBMS). versatile, flexible database and is currently On the other hand, NoSQL (Not Only SQL) used today as the backend data store of databases store schema-less, unstructured many high-profile businesses and data in multiple collections and nodes. Non- organizations such as Forbes, Facebook, relational databases don’t need fixed table Google, IBM, Twitter, and many more. schemas. NoSQL databases are scaled horizontally and support limited join queries. MongoDB  Is MongoDB a database? MongoDB is an open-source NoSQL database management program. NoSQL is used as an alternative to traditional relational databases. NoSQL databases are quite useful for working with large sets of distributed data. MongoDB is a tool that can manage document- oriented information, store or retrieve information. Overall, MongoDB is a good database, provided it suits your use case. If it does not, it can get very ugly. Try using it in the wrong place and you will get burned.