Is there a way I can generate a database schema from an erlang application like I can do with hibernate.
I assume you mean Mnesia, and if that is the case, you don't really understand the nature of the Mnesia database. It is by its very design and implementation "schemaless". You might could write some really messy ugly code that walked a Mnesia database and tried to document the various records that are in it, but that would be pretty much a futile exercise. If you are storing Records in Mnesia, you already have the "schema" in the .hrl files that the Records are defined in.
There's nothing like nhibernate for sql databases in erlang.
Check out SumoDB
Overview
sumo_db gives you a standard way to define your db schema, regardless of the db implementation (mongo, mysql, redis, elasticsearch, etc.).
Your entities encapsulate behavior in code (i.e. functions in a module) and state in a sumo:doc() implementation.
sumo is the main module. It translates to and from sumo internal records into your own state.
Each store is managed by a worker pool of processes, each one using a module that implements sumo_store and calls the actual db driver (e.g: sumo_store_mnesia).
Some native domain events are supported, that are dispatched through a gen_event:notify/2 automatically when an entity is created, updated, deleted. Also when a schema is created and when all entities of a given type are deleted. Events are described in this article.
Full conditional logic support when using find_by/2 and delete_by/2 function. You can find more information about the syntax of this conditional logic operators here.
Support for sorting (asc or desc) based on multiple fields unsing find_by/5 and find_all/4 functions. For example this [{age, desc}, {name, asc}]] will sort descendently by age and ascendently by name.
Support for docs/models validations through sumo_changeset (check out the Changeset section).
If you are looking for Java hibernate type of object to SQL mapping framework in Erlang, you may have to write your own mapping module. One option is to map Erlang records to SQL. Any framework has to make sure the type mapping. Here is the link to Erlang's ODBC mapping http://erlang.org/doc/apps/odbc/databases.html#type
Erlang's ETS and Mnesia which is an extension of ETS are very flexible and efficient to manage records. If these two databases cannot be your choice, you might have to implement ways for record mapping
Related
I want to learn how practical using an LDAP server (say AD) as a storage base. To be more clear; how much does it make sense using an LDAP server instead of using RDBMS to store data?
I can guess that most you might just say "it doesn't" but there might be some reasons to make it meaningful (especially business wise);
A few points first;
Each table becomes a container entity and each row becomes a new entity as a child. Row entities contains attributes for columns. So you represent your data in this way. (This should be the most meaningful representation I think, suggestions are welcome)
So storing data like a DB server is possible but lack of FK and PK (not sure about PK) support is an issue. On the other hand it supports attribute (relates to a column) indexing (Not sure how efficient). So consistency of data is responsibility of the application layer.
Why would somebody do this ever?
Data that application uses/stores closely matches with the existing data in AD. (Users, Machines, Department Info etc.) (But still some customization is required to existing entity schema, and new schema definitions are needed for not very much related data.)
(I think strongest reason would be this: business related) Most mid-sized companies have very well configured AD servers (replicated, backed-up etc.) but they don't have such DB setup (you can make comment to this as much as you want). Say when you sell your software which requires a DB setup to these companies, they must manage their DB setup; but if you say "you don't need DB setup and management; you can just use existing AD", it sounds appealing.
Obviously there are many disadvantages of giving up using DB, feel free to mention them but let's assume they are acceptable. (I can mention more if question is not clear enough.)
LDAP is a terrible tool for maintaining most business data.
Think about a typical one-to-many relationship - say, customer and orders. One customer has many orders.
There is no good way to represent this data in an LDAP directory.
You could try having a mock "foreign key" by making every entry of that given object class have a "foreign key" attribute, but your referential integrity just went out the window. Cascade deletes are impossible.
You could try having a "customer" object that has "order" children. However, you've just introduced a specific hierachy - you're now tied to it.
And that's the simplest use case. Once you start getting into more complex relationships, you're basically re-inventing an RDBMS in a system explicity designed for a different purpose. The clue's in the name - directory.
If you're storing a phonebook, then sure, use LDAP. For anything else, use a real database.
For relatively small, flexible data sets I think an LDAP solution is workable. However an RDBMS provides a number significant advantages:
Backup and Recovery: just about any database will provide ACID properties. And, RDBMS backups are generally easy to script and provide several options (e.g. full vs. differential). Just don't know with LDAP, but I imagine these qualities are not as widespread.
Reporting: AFAIK LDAP doesn't offer a way to JOIN values easily, much the less do things like calculate summations. So you would put a lot of effort into application code to reproduce those behaviors when you do need reporting. And what application doesn't ultimately?
Indexing: looks like LDAP solutions have indexing, but again, seems hit or miss. Whereas seemingly all databases out there have put some real effort into getting this right.
I think any serious business system's storage should be backed up in the same fashion you believe LDAP is in most environments. If what you're really after is its flexibility in terms of representing hierarchy and ability to define dynamic schemas I'd suggest looking into NoSQL solutions or the Java Content Repository.
LDAP is very usefull for storing that information and if you want it, you may use it. RDMS is just more comfortable with ORM systems. Your persistence logic with LDAP will so complex.
And worth mentioning that this is not a standard approach -> people who will support the project will spend more time on analysis.
I've used this approach for fun, i generate a phonebook from Active Directory, but i don`t think that it's good idea to use LDAP as a store for business applications.
In short: Use the right tool for the right job.
When people see LDAP you already set an expectation on your system. Don't forget that the L Lightweight. LDAP was designed for accessing directories over a network.
With a “directory database” you can build a certain type of application. If you can map your data to a tree like data structure it will work. I surely would not want to steam videos from LDAP! You can probably hack something but I would prefer a steaming server..
There might be some hidden gotchas down the line if you use a tool not designed for what it is supposed to do. So, the downside is you'll have to test stuff that would have been a given in some cases.
It's not is not just a technical concern. Your operational support team might “frown” on your application as they would have certain expectations/preconceptions based on your applications architectural nature. Imagine their surprise if you give them CRM system (website + files and popped email etc.) in a LDAP server as database to maintain.
If I was in your position, I would steer towards one of the NoSQL db solutions rather than trying to use LDAP. LDAP is fine for things like storing user and employee information, but is terrible to interact with when you need to make changes. A NoSQL db will allow you to store your data how you want without the RDBMS overhead you would like to avoid.
The answer is actually easy. Think of CRUD (Create, Read, Update, Delete). If a lot of Read will be made in your system, you can think of using LDAP. Because LDAP is quick in read operations and designed so. If the other operations will be made more, the RDMS would be a better option.
I'm working on a MUD (Multi User Dungeon) in Python and am just now getting around to the point where I need to add some rooms, enemies, items, etc. I could hardcode all this in, but it seems like this is more of a job for a database.
However, I've never really done any work with databases before so I was wondering if you have any advice on how to set this up?
What format should I store the data in?
I was thinking of storing a Dictionary object in the database for each entity. In htis way, I could then simply add new attributes to the database on the fly without altering the columns of the database. Does that sound reasonable?
Should I store all the information in the same database but in different tables or different entities (enemies and rooms) in different databases.
I know this will be a can of worms, but what are some suggestions for a good database? Is MySQL a good choice?
1) There's almost never any reason to have data for the same application in different databases. Not unless you're a Fortune500 size company (OK, i'm exaggregating).
2) Store the info in different tables.
As an example:
T1: Rooms
T2: Room common properties (aplicable to every room), with a row per **room*
T3: Room unique properties (applicable to minority of rooms, with a row per property per room - thos makes it easy to add custom properties without adding new columns
T4: Room-Room connections
Having T2 AND T3 is important as it allows you to combine efficiency and speed of row-per-room idea where it's applicable with flexibility/maintanability/space saving of attribute-per-entity-per-row (or Object/attribute/value as IIRC it's called in fancy terms) schema
Good discussion is here
3) Implementation wise, try to write something re-usable, e.g. have generic "Get_room" methods, which underneath access the DB -= ideally via transact SQL or ANSI SQL so you can survive changing of DB back-end fairly painlessly.
For initial work, you can use SQLite. Cheap, easy and SQL compatible (the best property of all). Install is pretty much nothing, DB management can be done by freeware tools or even FireFox plugin IIRC (all of FireFox 3 data stores - history, bookmarks, places, etc... - are all SQLite databases).
For later, either MySQL or Postgres (I don't do either one professionally so can't recommend one). IIRC at some point Sybase had free personal db server as well, but no idea if that's still the case.
This technique is called entity-attribute-value model. It's normally preferred to have DB schema that reflects the structure of the objects, and update the schema when your object structure changes. Such strict schema is easier to query and it's easier to make sure that the data is correct on the database level.
One database with multiple tables is the way to do.
If you want a database server, I've recommend PostgreSQL. MySQL has some advantages, like easy replication, but PostgreSQL is generally nicer to work with. If you want something smaller that works directly with the application, SQLite is a good embedded database.
Storing an entire object (serialized/encoded) as a value in the database is bad for querying - I am sure that some queries in your mud will NOT need to know 100% of attributes, or may retrieve a list of object by a value of attributes.
it seems like this is more of a job
for a database
True, although 'database' doesn't have to mean 'relational database'. Most existing MUDs store all data in memory, and read it in from flat-file saved in a plain-text data format. I'm not necessarily recommending this route, just pointing out that a traditional database is by no means necessary. If you do want to go the relational route, recent versions of Python come with sqlite which is a lightweight embedded relational database with good SQL support.
Using relational databases with your code can be awkward. Any change to a game logic class can require a parallel change to the database, and changes to the code that read and write to the database. For this reason good planning will help you a lot, but it's hard to plan a good database schema without experience. At least get your entity classes planned first, then build a database schema around it. Reading up on normalizing a database and understanding the principles there will help.
You may want to use an 'object-relational mapper' which can simplify a lot of this for you. Examples in Python include SQLObject, SQLAlchemy, and Autumn. These hide a lot of the complexities for you, but as a result can hide some of the important details too. I'd recommend using the database directly until you are more familiar with it, and consider using an ORM in the future.
I was thinking of storing a Dictionary
object in the database for each
entity. In htis way, I could then
simply add new attributes to the
database on the fly without altering
the columns of the database. Does that
sound reasonable?
Unfortunately not - if you do that, you waste 99% of the capabilities of the database and are effectively using it as a glorified data store. However, if you don't need aforementioned database capabilities, this is a valid route if you use the right tool for the job. The standard shelve module is well worth looking at for this purpose.
Should I store all the information in
the same database but in different
tables or different entities (enemies
and rooms) in different databases.
One database. One table in the database per entity type. That's the typical approach when using a relational database (eg. MySQL, SQL Server, SQLite, etc).
I know this will be a can of worms,
but what are some suggestions for a
good database? Is MySQL a good choice?
I would advise sticking with sqlite until you're more familiar with SQL. Otherwise, MySQL is a reasonable choice for a free game database, as is PostGreSQL.
One database. Each database table should refer to an actual data object.
For instance, create a table for all items, all creatures, all character classes, all treasures, etc.
Spend some time now and figure out how objects will relate to each other, as this will affect your database structure. For example, can a character have more than one character class? Can monsters have character classes? Can monsters carry items? Can rooms have more than one monster?
It seems pedantic, but you'll save yourself a whole lot of trouble early by figuring out what database objects "belong" to which other database objects.
Background: Okay, so I'm looking for what I guess is an object database. However, the (admittedly few) object databases that I've looked at have been simple persistence layers, and not full-blown DBMSs. I don't know if what I'm looking for is even considered an object database, so really any help in pointing me in the right direction would be very appreciated.
I don't want to give you two pages describing what I'm looking for so I'll use an example to illustrate my point. Let's say I have a "BlogPost" object that I need to store. Something like this, in pseudocode:
class BlogPost
title:String
body:String
author:User
tags:List<String>
comments:List<Comment>
(Assume Comment is its own class.)
Now, in a relational database, author would be stored as a foreign key pointing to a User.id, and the tags and comments would be stored as one-to-many or many-to-many relationships using a separate table to store the relationships. What I'd like is a database engine that does the following:
Stores related objects (author, tags, etc.) with a direct reference instead of using foreign keys, which require an additional lookup; in other words, objects on top of each other should be natively supported by the database
Allows me to add a comment or a tag to the blog post without retrieving the entire object, updating it, and then putting it back into the database (like a document-oriented database -- CouchDB being an example)
I guess what I'm looking for is a navigational database, but I don't know. Is there anything even remotely similar to what I'm thinking of? If so, what is it called? (Or better yet, give me an actual working database.) Or am I being too picky?
Edit:
Just to clarify, I am NOT looking for an ORM or an abstraction layer or anything like that. I am looking for an actual database that does this internally. Sorry if I'm being difficult, but I've searched and I couldn't find anything.
Edit:
Also, something for the JVM would be excellent, but at this point I really don't care what platform it runs on.
I think what you are describing could easily be modeled in a graph database. Then you get the benefit of navigating to the nodes/edges where you want to make changes without any need to retrieve anything else. For the JVM there's the Neo4j open source graph database (where I'm part of the team). You can read about it over at High Scalability, as part of an overview at thinkvitamin or in this stackoverflow thread. As for the tags, I think storing them in a graph database can give you some extra advantages if you want to find related tags and similar stuff. Just drop a line on the mailing list, and I'm sure the community will help you out.
You could try out db4o which is available in C# and Java.
I think our looking for this: http://www.odbms.org/. This site has some good info on Object Databases, including Objectivity, which is a pretty good object database.
Elephant does this: http://common-lisp.net/project/elephant/
Exactly what you've described can be done with (N)Hibernate running on an ordinary RDBMS.
The advantage of using such a persistence layer with an ordinary database is that you have a standard database system combined with convenient programming. You declare your classes in a very natural way, and (N)Hibernate provides a way to translate betweeen references/lists and foreign key relationships.
Java tutorial: http://docs.jboss.org/hibernate/stable/core/reference/en/html/tutorial-firstapp.html
.NET tutorial: https://web.archive.org/web/20081212181310/http://blogs.hibernatingrhinos.com/nhibernate/archive/2008/04/01/your-first-nhibernate-based-application.aspx
If you insist that you don't want to use a well-supported standard RDBMS and would rather trust your data to something more exotic and less heavily tested, you're looking for an Object Relational Database.
However, such a product would probably be best implemented by making it be a layer over a standard RDBMS anyway. This is probably why ORMs like (N)Hibernate are the most popular solution - they allow standard RDBMS software (and widely available management/user skills) to be applied, and yet the programming experience is 99% object-based.
This is exactly what LINQ was designed for.
Microsoft LINQ defines a set of proprietary query operators that can be used to query, project and filter data in arrays, enumerable classes, XML (XLINQ), relational database, and third party data sources. While it allows any data source to be queried, it requires that the data be encapsulated as objects. So, if the data source does not natively store data as objects, the data must be mapped to the object domain. Queries written using the query operators are executed either by the LINQ query processing engine or, via an extension mechanism, handed over to LINQ providers which either implement a separate query processing engine or translate to a different format to be executed on a separate data store (such as on a database server as SQL queries (DLINQ)). The results of a query are returned as a collection of in-memory objects that can be enumerated using a standard iterator function such as C#'s foreach.
There's a variety of terms, all linked to Object-Relational Mapping, aka ORM, which is probably going to be the most useful one for you to look up. ORM libraries exist for many programming languages.
Oracle's nested tables provide some part of that functionality, though in updates, you cannot just add a row to the nested table - you have to replace the whole nested table.
I guess you're looking for an ORM with "EntityFirst" approach.
In EntityFirst approach the developer is least[not-at-all] concerned with Database. You just have to build your entities or objects. The ORM then takes care of storing the entities in Database and retrieving them at your will.
The only EntityFirst ORM witihn my knowledge "Signum". It's a wonderful framework built on top of .net. I recommend you to go thrgouh some videos on the SignumFramework website and I'm sure you'll find it useful.
Link Text: http://www.signumframework.com
Thanks.
ZODB perhaps?
good introduction find here:
http://www.ibm.com/developerworks/aix/library/au-zodb/
You could try out STSdb, DB4O, Perst ... which is available in C# and Java.
I'm looking for some feedback on the best approach to a problem I've been tasked with. There are two systems with their own databases which store very similar business entities.
For each entity in question there needs to be a synchronization mechanism in place to make sure that changes in one database are delivered to the other when a change occurs and for the changes to be translated into the destination table structure. This translation means that replication is not an option but I don't want to start writing bespoke triggers or views etc to keep them in sync.
Is this something which BizTalk or a similar product could handle after an initial configuration / mapping process? Also, is Biztalk potentially overkill and are there any other methods which I could employee to achieve this?
Thanks,
Brian.
It depends on the size of the "systems" (tables ?) to synchronise.
EAI are the general application to do this. Connecting two systems which can't interact together, effectivly mapping one business object to another one, aplling a map to translate one into another.
But such tools (like webMethods for exemple) are entreprise tools, if you only need to synchronise two table from two systems EAI will clearly be overkill.
Anyway the principles can help you. The EAI approach would be to have a generic business object that's match all of properties found in both systems for the business objects you want to syncrhonise. Then you will have to have some sort of map to translate each application specific business objet to and from you generic business object. Your object should not only describe the business data, but also the operation to perform (create, update, delete data).
Then you need a trigger (or two if you want to synchronyze both ways) to detect when a change happen, use the map to transform the data your trigger get to generic object (with the operation to perform at the other end).
And finally you need an "updater" that will take the specific business object and do the right operation in the database (insert/update/delete)
EAI provide connectors to take care of triggering the workflow and updating the database. You will still need to define some mappings in some specific way depending of the EAI used.
EAI are a lot more powerfull than juste synchronizing two tables. Connnectors have various type and can interact with various system (proprietary ones), various database, simple format (xml, text) or specific protocols (ftp, webservices, etc.)
EAI also ensure that any modification is effectivly commited at the end.
Hope it helps.
Sql Server Integration Services could be a cheep candidate for solving the problem (can connect to other DBs and data sources that Sql Server). SSIS is part of all Sql Server installations (with the exception of Express).
There is a nifty tool called "datariver" by the Swiss company Sowatec (where I did work a few years ago. I wasn't involved with this product though; just so you know). It's meant to flow data from sources to sinks (just like a river).
The web site is in German but the guys behind it are happy to answer any of your questions in English by mail.
BizTalk is and would be an ideal solution for this kind of problem.
What BizTalk can do?
1. Define a schema which represents a common business entity, this is essentially all the fields which need to be in sync across several database tables.
Define the flow of communication (Orchestrations) and end-points(web services), i.e. which update triggers what changes!
Use maps to map the common business entity into specific data elements required
by the databases. Note that biztalk has built-in adapters to speed up the development process.
Adequate time must be spent in design and of this system the results would be fabulous.
For development purposes refer my articles (google keywords: Biztalk + Karamchetti)
What are the other types of database systems out there. I've recently came across couchDB that handles data in a non relational way. It got me thinking about what other models are other people is using.
So, I want to know what other types of data model is out there. (I'm not looking for any specifics, just want to look at how other people are handling data storage, my interest are purely academic)
The ones I already know are:
RDBMS (mysql,postgres etc..)
Document based approach (couchDB, lotus notes)
Key/value pair (BerkeleyDB)
db4o
Quote from the "about" page:
db4o is the open source object database that enables Java and .NET developers to store and retrieve any application object with only one line of code, eliminating the need to predefine or maintain a separate, rigid data model.
Older non-relational databases:
Network Database
Hierarchical Database
Both mostly went out of style when relational became feasible.
Column-oriented databases are also a bit of a different animal. Many of them do support standard relational database SQL though. These are generally used for data warehouse type applications.
Semantic Web is also a non-relational data storage paradigm. There are no relations, all metadata is stored in the same way as data, and every entity has potentially its own unique set of attributes. Open-source projects that implement RDF, a Semantic Web standard, include Jena and Sesame.
Isn't Amazon's SimpleDB non-relational?
db4o, as mentioned by Eric, is an Object-Oriented database management system (OODBMS).
There's object-based databases(Gemstore, for example). Google's Big-Table and Amason's Simple Storage I am not sure how you would categorize, but both are map-reduce based.
A non-relational document oriented database we have been looking at is Apache CouchDB.
Apache CouchDB is a distributed, fault-tolerant and schema-free document-oriented database accessible via a RESTful HTTP/JSON API. Among other features, it provides robust, incremental replication with bi-directional conflict detection and resolution, and is queryable and indexable using a table-oriented view engine with JavaScript acting as the default view definition language.
Our interest was in providing a distributed access user preferences store that would be immune to shape changes to which we could serialize preference objects from Java and access those just as easily with Javascript from a XULRunner based client application.
I'd like to detail more on Bill Karwin's answer about semantic web and triplestores, since it's what I am working on at the moment, and I have something to say on it.
The idea behind a triplestore is to store a graph-based database, whose datamodel roots in RDF. With RDF, you describe nodes and associations among nodes (in other words, edges). Data is organized in triples :
start node ----relation----> end node
(in RDF speech: subject --predicate--> object). With this very simple data model, any data network can be represented by adding more and more triples, provided you give a meaning to nodes and relations.
RDF is very general, and it's a graph-based data model well suited for search criteria looking for all triples with a particular combination of subject, predicate, or object, in any combination. Eventually, through a query language called SPARQL, you can also perform more complex queries, an operation that boils down to a graph isomorphism search onto the graph, both in terms of topology and in terms of node-edge meaning (we'll see this in a moment). SPARQL allows you only SELECT (and similar) queries. No DELETE, no INSERT, no UPDATE. The information you query (e.g. specific nodes you are interested in) are mapped into a table, which is what you get as a result of your query.
Now, topology in itself does not mean a lot. For this, a Schema language has been invented. Actually, more than one, and calling them schema languages is, in some cases, very limitative. The most famous and used today are RDF-Schema, OWL (Lite and Full), and they predate from the obsolete DAML+OIL. The point of these languages is, boiling down stuff, to give a meaning to nodes (by granting them a type, also described as a triple) and to relationships (edges). Also, you can define the "range" and "domain" of these relationships, or said differently what type is the start node and what type is the end node: you can say for example, that the property "numberOfWheels" can be applied only to connect a node of type Vehicle to a non-zero integer value.
ns:MyFiat --rdf:type--> ns:Vehicle
ns:MyFiat --ns:numberOfWheels-> 4
Now, you can use these ontologies in two directions: validation and inference. Validation is not that fancy today, but I've seen instances of use. Inference is what is cool today, because it allows reasoning. Inference basically takes a RDF graph containing a set of triples, takes an ontology, mixes them into a triplestore database which contains an "inference engine" and like magic the inference engine invents triples according to your ontological description. Example: suppose you just store this information in the database
ns:MyFiat --ns:numberOfWheels--> 4
and nothing else. No type is specified about this node, but the inference engine will add automatically a triple saying that
ns:MyFiat --rdf:type--> ns:Vehicle
because you said in your ontology that only objects of type Vehicle can be described by a property numberOfWheels.
Conversely, you can use the inference engine to validate your data against the ontology so to refuse not compliant data (sort of like XML-Schema for XML). In this case, you will need both triples to have your data successfully accepted by the triplestore.
Additional characteristics of triplestores are Formulas and Context-aware storage. Formulas are statements (as usual, triples subject predicate object) that describe something hypothetical. I never used Formulas, so I won't go into more details of something I don't know. Context awareness are basically subgraphs: the problem with storing triples is that you don't have anything to say where these triples come from. Suppose you have two dealers that describe the same price of a component. One says that the price is 5.99 and the other 4.99. If you just store both triples into a database, now you don't know anything about who stated each information. There are two ways to solve this problem.
One is reification. Reification means that you store additional triples to describe another triple. It's wasteful, and makes life hell because you have to reify every and each triple you store. The alternative is context-awareness. Having a context-aware storage It's like being able to box a bunch of triples into a container with a label on it (the context identifier). You now can use this identifier as subject for additional statements, hence describing a bunch of triples in a single action.
4. Navigational. Includes Tree/Hierarchy and Graph/Network.
File systems, the semantic web, XML, Object databases, CODASYL, and many others all fit into this category.
Those 4 are pretty much it.
There is also what is referred to as an "inverted index" or "inverted list" database. Software AG's Adabas product would be an example. As with hierachical, these databases continue to be used in large corporate or university environments because of legacy considerations or due to a performance advantage in certain situations (typically high-end transactional applications).
There are BASE systems (Basically Available, Soft State, Eventually consistent) and they work well with simple data models holding vast volumes of data. Google's BigTable, Dojo's Persevere, Amazon's Dynamo, Facebook's Cassandra are some examples.
See LINK
The illuminate Correlation Database is a new revolutionary non-relational database. The Correlation Database Management Dystem (CDBMS) is data model independent and designed to efficiently handle unplanned, ad hoc queries in an analytical system environment. Unlike relational database management systems or column-oriented databases, a correlation database uses a value-based storage (VBS) architecture in which each unique data value is stored only once and an auto-generated indexing system maintains the context for all values (data is 100% indexed). Queries are performed using natural language instead of SQL (NoSQL).
Learn more at: www.datainnovationsgroup.com