Data Services In Southaven MS At NW Database Services
Data Cleaning, Data Cleansing, Data Scrubbing, Deduplication, Data Transformation, NCOA, Mail PreSorts, Email Verification, Email Append, & Phone Append Services in Southaven Mississippi
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We Are A Full Service Data Services That Can Help You Run Your Business
Northwest Database Services is a full-spectrum data service that has been performing data migration, data scrubbing, data cleaning, and de-duping data services for databases and mailing lists, for over 34 years. NW Database Services provides data services to all businesses, organizations, and agencies in Southaven MS and surrounding communities.
What We Do
When you need your data to speak to you regarding your business’s trends, buying patterns or just whether or not your customers are still living.
We provide data transformation services for Extract, Transform and Load (ETL) operations typically used in data migration or restoration projects.
Duplication of data plagues every database and mailing list. Duplication is inevitable, constantly keeps growing and erodes the quality of your data.
Direct Mail - Presorts
It’s true the United States Postal Service throws away approximately thirty five percent of all bulk mail every year! Why so much? Think: “Mailing list cleanup.
We Are Here To Help!
Woodland, WA 98674
To use email, remove the brackets
Information About Data Cleaning And Data Services
What Is Structured Data?
Structured data refers to data that fits within a predefined data structure. It is a predefined data model that defines data types and access rules. Structured data can be any clearly labeled information database (such as an Excel file or SQL database) that is clearly identified. These data are stored in tables with clear relationships between rows and columns. It is easy to analyze and mine this data. SQL (Structured Query Language) is a common tool for this purpose.
Structured data can be easily sorted and broken down into its components. Let’s take, for example, a customer email campaign. There may be a lot of customer information in your customer relationship management system (CRM). This could include phone numbers, invoices, and history of interactions. It is easy to find the information you need because the data has been properly organized.
Structured data can be described as quantitative data. It contains quantifiable numeric values, such as dates, times, numbers, etc. It can also contain characters and other non-numeric data. These are stored as encrypted strings. This means that even though the data might be text-based it is represented using numerical units that a machine can understand.
Structured data is usually stored in order, cleaned and ordered. This means that it takes up less space than raw data. It is generally easier to secure if stored in robust systems. According to some estimates, 20% of enterprise data are not in a structured format. Structured data is best handled by data analysts, but it’s the unstructured data that requires constant housekeeping.
What Is Unstructured Information?
Unstructured data, also known as “big data” or “raw data”, is data that doesn’t have a predefined format. It is usually large in volume, heavy in text, and stored in its native format, known as data lakes. Unstructured data is difficult to secure and requires large amounts of storage space. It’s also much more difficult for computers and humans to understand because it isn’t stored in relational database.
Unstructured data can be in many formats. Images, audio, video and spreadsheets are just a few examples of unstructured data. Structured versus unstructured data can be seen in real life as the date and the time of an email (structured) and the email content (unstructured). The first is easier to understand, store in databases, and extract meaning from. Although the latter can be also parsed, it is more difficult to make sense of than just storing it in an orderly manner.
It is impossible to analyze unstructured data if there aren’t clear parameters or encoding. Normally, multiple rounds of data manipulation and parsing are necessary (commonly using machine-learning algorithms).
Northwest Database Services has 34+ years experience with all types of data services, including mail presorts, NCOA, and data deduplication. If your database systems are not returning poor data, it is definitely time for you to consult with a data services specialist. We have experience with large and small data sets. Often, data requires extensive manipulation to remove corrupt data and restore the database to proper functionality. Call us at (360)841-8168 for a consultation and get the process of data cleaning started as soon as possible.
NW Database Services
404 Insel Rd
Woodland WA 98674
City of Southaven MS Information
Southaven, Mississippi, United States, is a city located in DeSoto County. It is the principal city of Greater Memphis. Southaven was the third-largest Mississippi city and the second-most populous suburb of Memphis, according to the 2020 census. The I-55/I-69 freeway traverses Southaven from north to south. Southaven, a Memphis neighborhood, is the reason for its name.
Southaven was originally a village that Kemmons Wilson, a Memphis homebuilder, wanted to create a few subdivisions with small starter homes. He did this by moving from Whitehaven, Tennessee (now Memphis) across the Mississippi border. Memphis eventually annexed Whitehaven in the 1970s. Southaven, which was officially incorporated in 1980 is one of the fastest growing cities in the southeast United States.  Southaven has doubled its land and tripled its population in just 20 years.
Southaven has a subtropical humid climate with an average annual rainfall of almost 55 inches (1.400 mm). This is evenly distributed throughout the year. April is the wettest month, while August is the driest. The average high temperature in July is 92 degrees F (33 degrees C) and 49 degrees F (9 degC) respectively.
The city was home to 48,982 residents and 13,125 families as of 2010. It had 1,499.9 people per square mile (579.1/km2). The average density of 19,101 housing units was 339.3/square mile (131.0/km2).