Early DBMS have following problems·        Real World entities are not represented properlybecause normalization leads to relations that do not correspond to real worldentities.·        Relation is the only construct that is used torepresent data and data relationships.·        Early DBMS have only a fixed set of operationsand it cannot be extended·        Recursive queries are not supported if the depthlevel of recursion is not known.

·        Transactions are short lived and concurrencycontrols are not suited for long lived transactions. ·        Most of the DMLs are effected by computationalincompleteness. This limitation can be overcome by embedding SQL in higherlevel 3GLs but it creates impedance mismatch.·        Schema changes are difficult.·        Early DBMS are poor at navigational access.               Limitations in quality consideration            Dataquality explains the condition of a data set of qualitative or quantitativevariable.

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Data quality is high if the data is fit for use in planning, decisionmaking and operations. Another measure of quality is the correctness of representationa real life object. Increasing Size of data introduce another measure for dataquality which is data consistency. Different aspects of Data Quality are:·        Accuracy·        Completeness·        Update status·        Relevance·        Consistency across data sources·        Reliability·        Appropriate presentation·        Accessibility   Future and emerging aspects of quality in DBMS DesignTrends come and go, but many new concepts for databasemanagement are not flavor-of-the-month fads but have staying power, as well asthe power to transform organizations.

 What are the current trends in database management and howcan you best take advantage of them to benefit your organization? In anutshell, the current trends we’ve found are:     Databases thatbridge SQL/NoSQL    Databases in thecloud/Platform as a Service    Automatedmanagement    An increased focuson security