Data Solutions can be a very broad term – encompassing a lot of moving parts. As a whole it is an umbrella term that covers a variety of solutions to make your data work better for you. The purpose of these solutions are to provide businesses with a way to facilitate the influx of data received into actionable data. Like its name suggests, actionable data helps you know how to formulate business plans, marketing efforts, and helps you manage customer databases – the use cases are endless. Every business has data – but does your data work for you?

New to the data world? We understand – we’ve compiled a list of data terms and explanations you need to know if you’re just starting out.

Actionable data – information that can be acted upon or information that gives enough insight into the future that the actions that should be taken become clear for decision makers.

API (Application program interface) – a set of instructions on how to access and build web-based software applications.

Big data – This refers to the vast amounts of structured and unstructured data that can come from a myriad of sources. Small data can be managed more easily, tying in with the idea presented by Allen Bonde that “big data is for machines; small data is for people”.

Big Data Scientist – Someone who can develop the algorithms to make sense out of big data.

Business Intelligence (BI) – The general term used for the identification, extraction, and analysis

Dashboard – A graphical representation of the analyses performed by the algorithms

Data aggregation – The act of collecting data from multiple sources for the purpose of reporting or analysis.

Data architecture and design – How enterprise data is structured. The actual structure or design varies depending on the eventual end result required. Data architecture has three stages or processes: conceptual representation of business entities. the logical representation of the relationships among those entities, and the physical construction of the system to support the functionality.

Database – A digital collection of data and the structure around which the data is organized.

Database administrator (DBA) – A person, often certified, who is responsible for supporting and maintaining the integrity of the structure and content of a database.

Data cleansing – The act of reviewing and revising data to remove duplicate entries, correct misspellings, add missing data, and provide more consistency.

Data collection – Any process that captures any type of data.

Data integrity – The measure of trust an organization has in the accuracy, completeness, timeliness, and validity of the data.

Data migration – The process of moving data between different storage types or formats, or between different computer systems.

Data mining – The process of deriving patterns or knowledge from large data sets.

Data science – a discipline that incorporates statistics, data visualization, computer programming, data mining, machine learning, and database engineering to solve complex problems.

Data Visualization – the graphical representation of information and data.

Data warehouse – a digital repository where businesses store their data for the purpose of reporting and analysis.

Encryption – The conversion of data into code to prevent unauthorized access.

SingleStore (formerly MemSQL) – a distributed, relational, SQL database management system known for speed in data ingestion, transaction processing, and query processing.

Metadata – Data that describes other data. This information is used by search engines to filter through documents and generate appropriate matches.

MySQL – most popular open source database. Mysql has different variants : MariaDB, Aurora, Percona and more. For each of them, the main engine is the same: innodb

RDS Mysql – A full managed database in AWS. Backup, restore, replication are handled via a few clicks via a browser interface.

Python – a general-purpose coding language. Unlike HTML, CSS, and JavaScript, it can be used for other types of programming and software development besides web development. It can handle a large range of tasks and is considered a very beginner-friendly language.

SaaS – Software-as-a-service – a software distribution model that allows a service provider to deliver applications to a customer via the internet.

Systems of record – Transactions, highly stateful, which demand absolute consistency and transactional integrity regardless of the value of an individual transaction (the state of an airline seat, for example, must be exact and must show consistently to every querying entity).

Tableau – software that can be used for data visualization.

At Data-Sleek we understand how daunting the data world can seem when you’re first introduced to it. We’re here to help you navigate your options and build customized solutions based on your unique business and needs.

Igor

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