His erratic behaviour over the years had come to the attention of law enforcement on at least 105 occasions without triggering a response, Faeser added.
The figure, compiled after the December 20th attack, showed the need for "better data management by the federal and state security authorities", Faeser said.
"Police data must be centrally and securely bundled" to identify threats, she told journalists at an event to commemorate the victims in the eastern city of Magdeburg.
The suspect, 50-year-old Saudi psychiatrist Taleb al-Abdulmohsen, who had lived in Germany for 18 years, was arrested at the scene of the ramming, which left six people dead and over 200 wounded.
Investigators had pieced together the profile of a perpetrator who suffered "psychological issues" and was "influenced by incoherent conspiracy theories", Faeser said.
The suspect was "massively Islamophobic and close to right-wing extremist ideologies", she added, and "His hatred is directed against both the German state and against individuals."
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A large amount of information on the suspect had been available before the attack, including a slew of social media posts, Faeser said.
However, "no one had all of the facts", she said.
The lack of oversight was among the factors that kept authorities from intervening early to stop the attack, she said.
As well as centralising data from different federal and regional authorities, "large amounts of data must also be able to be analysed using AI" in future, she said.
"We also need new, more precise criteria and action plans to assess the danger posed by people who do not fit the existing mould."
The attack in Magdeburg came almost eight years to the day after another at a Christmas market in 2016, when a lorry ploughed into a crowd in Berlin.
The previous attack, which left 13 people dead, was carried out by a Tunisian jihadist and claimed by the Islamic State group.
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